Precision motion control is essential for the reliable and efficient operation of industrial and autonomous systems. This article presents an adaptive neural network (NN) controller that achieves high-accuracy trajectory tracking and disturbance rejection in the presence of nonlinear effects, such as cogging and friction forces. The key contribution lies in incorporating ahistory-of-error learning mechanisminto the NN objective function, enabling the controller to adapt based on both instantaneous and past tracking dynamics. This temporal formulation enhances learning efficiency and disturbance suppression compared to conventional instantaneous-error methods. The controller employs a single-layer feedforward NN to estimate unknown dynamics, with a modified backpropagation algorithm and e-modification ensuring stable weight adaptation. A Lyapunov-based stability analysis is presented that guarantees bounded tracking errors and weight convergence. The resulting control law achieves robust real-time implementation without compromising computational efficiency. Experimental results on a cylindrical robot subjected to friction and cogging torque disturbances show over 60% improvement in tracking accuracy and up to 40% enhancement in disturbance rejection relative to NN and proportional integral derivative (PID) baselines. These results confirm the effectiveness of the proposed history-enhanced adaptive neural control framework for precision motion systems.

Accurately predicting infectious disease dynamics is crucial for effective public health management and decision-making. Traditional epidemiological models, such as the Susceptible-Infected-Recovered (SIR) framework, often struggle to capture the complex and evolving nature of outbreaks due to their reliance on predefined system parameters. This paper presents a three-layer neural network (NN) model for real-time prediction of infectious disease dynamics without requiring prior knowledge of the system. Unlike conventional methods, the proposed NN incorporates an integral component into its update rules, allowing prediction accuracy to improve over time by accounting for both current and historical errors. The model is validated using both simulated SIR data and real-world infectious disease datasets, consistently demonstrating superior predictive accuracy. It outperforms baseline methods, including traditional and autoregressive networks, in both accuracy and adaptability, highlighting its potential for real-time forecasting and public health planning. The computational efficiency of the method makes it suitable for real-time applications in evolving disease environments.

This paper presents a multi-variable predictor feedback controller for a static, multi-input multi-output, daylight harvesting system affected by an uncertain input delay and unknown external disturbances. To this end, a predictor feedback control scheme is incorporated into a stabilizing feedback controller used in the absence of delay. The issues rising from delay estimation errors are discussed and heuristic stability and robustness analysis based on the root locus method is presented that facilitates the complicated task of controller design and tuning in presence of delay mismatch. The proposed analysis can be applied to systems of any order with time delay, regardless of their open-loop stability characteristics. Simulation results are presented to verify the effectiveness of the proposed analysis method and control scheme.

This article presents a neural network-based control method for daylight harvesting in a proof-of-concept greenhouse consisting of emulated sunlight and dimmable light emitting diode light fixtures. The objective of this multi-input-multi-output lighting system is to deliver desired levels of light, within a specific spectrum range, to locations of interest in a grow tent. To this end, a learning neural network controller with online adaptive weights is presented which can achieve stability with small errors in the presence of disturbances and modeling uncertainties. A stability analysis of the closed-loop system is presented along with a selection method for obtaining the control parameters. The neural controller is enhanced with an antiwindup mechanism to account for the nonlinear effect of actuator saturation. Experimental results are presented to verify the proposed daylighting control strategy which confirm analytic and simulation studies.

The aim of our study is to develop an intelligent control system for mixing color ratios using LED lights in a greenhouse environment. To this end, different components of an experimental testbed is presented for achieving the desired light requirements for plant growth in a greenhouse environment. The proposed testbed provides a easy-to-use plant growth system with IoT-enabled control and monitoring features. To testify the features mentioned above, a feedback lighting control method to achieve a desired photosynthetic photon flux density (PPFD) set point is implemented. A two-week experiment was conducted on microgreen kale which was planted in the testbed and harvested at the end of the experiment. The experimental results has shown that the tested microgreen kale grew with a healthy condition in the proposed testbed and lighting environment.

Parasitic torque pulsations existing in permanent magnet synchronous motors (PMSMs) degrade their performance, particularly at low speeds. In this paper, an adaptive iterative learning control (ILC) strategy is proposed for torque ripple minimization in a PMSM drive system. An analysis is conducted to study the impact of ILC gains on the steady-state and transient performance of the system. Accordingly, a real-time tuning method based on multi-variable sliding-mode extremum seeking (MSES) is proposed to adjust the ILC gains. The proposed controller is applied to a PMSM and its performance is verified by comparing the results with a similar controller using a non-adaptive ILC scheme. The results demonstrate the effectiveness of the proposed ILC scheme in achieving lower torque ripples and faster transient performance.

In particle accelerators it's important to have a stable accelerating system for the beams of particles. The accelerator cavity should be controlled under it's resonance frequency with no disturbance to get the best performance. The particles would be accelerated to the highest desired speed. The Detuning of superconducting radio frequency (SRF) cavities is mainly caused by the Lorentz force, which is the radiation pressure induced by a high radio frequency (RF) field, and environmental mechanical vibrations that induce undesirable interference signals referred to as microphonics. The above factors can be described by a second order differential equation of the mechanical vibration modes of the cavity. In this paper three dominant mechanical vibration modes for the system has been considered and a control scheme has been designed based on input-output linearization. The stability analysis system has been considered by defining a Lyapunov function. It is shown through simulation studies that the proposed control technique can successfully the suppress microphonic noise due to the SRF cavity's dynamics.

This paper presents a nonlinear model predictive control (MPC) method to solve the problem of regulating the suspension air gap in a magnetic levitation system in the presence of disturbances. The method iteratively linearizes the system model at each prediction step around the operating point. Then it finds linear matrix inequalities (LMI) describing upper bounds for the remaining nonlinearities and finally obtains the control signal by solving the LMIs and applying it to the original nonlinear system. A main advantage of the proposed method is that it removes the linear approximation error present in conventional linerarization-based NMPC methods.

This paper presents an intelligent crop monitoring system consisting of a controlled growing chamber, dimmable LED lights, imaging array, cloud data storage, and data processing components. The system is implemented using low-cost imaging sensors integrated with image recognition algorithms. A modified naive bayes classifier is developed for crop monitoring that estimates key color features of plants and utilizes them to identify plants as belonging to a specific plant type/class. The resulting data-base is continuously enhanced using the results of the analysis. Furthermore, the updated database is utilized to retrain the classifier periodically to account for the changing environmental and plant conditions. A series of experiments are presented that verify performance of the developed system.

In this paper, an adaptive PI controller using a multi-level DC link (MLDCL) inverter is proposed and applied for angular position trajectory tracking in a permanent magnet synchronous motor (PMSM) with relatively low stator inductance and resistance. Modern lightweight motors have smaller resistance and inductance values when compared to conventional motors, which give rise to higher levels of current ripples when using large PWM frequencies. To alleviate the problem, the proposed controller combines the merits of a multi-level DC link inverter with a multivariable sliding-mode extremum seeking tuned PI controller to achieve fast and precise trajectory tracking. The extremum seeking tuning method adjusts the PI gains in realtime which makes the system tracking performance more precise. The MLDCL inverter used in this paper reduces the PMSM current ripples of the three-phase inverter through utilizing multiple half-bridge cells instead of an individual DC source used in traditional pulse-width modulation (PWM) inverters. The tracking performance of the proposed control scheme is investigated through simulations by comparing the results with a recently proposed fixed-gain PI controller using a traditional PWM inverter. The results demonstrate the effectiveness of the proposed controller in achieving lower torque ripples and more precise tracking response.

This paper presents implementation of a Field Programmable Gate Array (FPGA) emulator for the Low Level Radio Frequency (LLRF) Normal conducting cavity at TRIUMF. Testing waveforms such as phase and amplitude in the cavity on the real hardware can be both difficult and dangerous. To allow testing of the real LLRF system in real time and also to obtain shorter processing time we need to have an effective hardware in the loop simulator of the cavity. Radio frequency(RF) cavity is equivalent to an electrical RLC circuit which acts like a second order filter model, therefore it is possible to emulate the cavity with an analog filter. But when it comes to digital field, the finite word length effect has to be considered and processed carefully. The discrete model of the cavity designed as an IIR bandpass Filter. The SIMULINK and MATLAB model of the cavity and their implementation are presented. An Altera DE4 development board was selected as the emulator of the cavity. And the result of digital designing of the cavity model on FPGA is presented.

This paper presents a neural network-based control method for achieving desired lighting levels in an LED-based lighting system with unknown or uncertain system model parameters in the presence of daylight disturbances. Assuming an unknown system model matrix, the control strategy utilizes an online neural network method to synthesize a learning controller. The control commands are dimming levels, which represent the percentage of LED's full power level and the outputs are illuminance levels at target points. The neural controller is designed using a Lyapunov-based analysis to achieve boundedness of the output error to an arbitrarily small ultimate bound. By considering the daylight as a disturbance, it serves as a bias for the desired control system set-point resulting in lower dimming command inputs and energy savings. The controller design only requires the tracking of error signal as input which eliminates the need for any prior knowledge of the daylight disturbance and room model.

In this paper, a novel Multivariable Sliding-mode Extremum Seeking (MSES) Proportional-Integral (PI) tuning method is proposed and its application is studied for torque control in a Permanent Magnet Synchronous Motor (PMSM). To this end, the stator three-phase currents are characterized by their maximum amplitude which directly controls the shaft torque. Hence, a PI controller is applied for controlling the maximum amplitude of the stator three phase currents. Due to requiring only one control loop to control the stator phase currents, the computational and implemental costs of the system reduce significantly when compared with conventional current controllers. Here, multivariable sliding-mode extremum seeking method is proposed as an optimization technique to tune parameters of the PI controller. This makes the PI current controller more efficient in terms of disturbance rejection and transient conditions. Furthermore, rotor position detection is conducted by applying Hall Effect sensors and using a continuous estimation method. This affects the switching sequence of a three-phase inverter connected to PMSM. The simulation results demonstrate the advantages of the proposed controller in terms of fast and precise convergence and robust performance in face of disturbances and uncertainties.

Cascaded H-bridge multilevel inverters have attracted considerable attention in applications such as reactive power compensation, solid-state transformers, and PV systems. The main disadvantage of CHBMLI in these applications is the imbalance of the DC capacitor voltages, especially in high-level inverters. The DC-link voltage unbalance increases the stress on the semiconductor devices and may cause serious damages. To overcome this issue, this paper presents a new DC-link capacitor voltage balancing method for CHBMLI. This method has a very effective and fast voltage balancing capability. Furthermore, the proposed algorithm is independent of the number of modules and voltage distribution; therefore, it could be applied to any CHBMLI regardless of its number of cells and levels without considerable modification. This method reduces computation efforts that makes it suitable for high-cell-number inverters. To verify the performance of the proposed modulation scheme, the proposed method is applied to a four-cell CHBMLI, utilized in STATCOM applications, using simulation studies through the PSCAD/EMTDC®software package. The simulation results show the effectiveness of the method.

A common problem with conventional alternator-based energy converters in vehicular applications is that they do not work at optimal operating points in their speed-power curves. This paper addresses the above problem by utilizing a Switched- Mode Rectifier (SMR) load-matching technique using real-time extremum seeking control. To this end, a multivariable control strategy is presented to track the maximum power in an alternator-based system. In particular, we propose a novel multivariable sliding-mode technique for maximum power point tracking (MPPT) in a Lundell alternator system. The proposed controller, combines the merits of multivariable extremum seeking and sliding-mode control. Utilizing the multivariable extremum seeking control makes the control model-free and increases the controller efficiency. Besides, the sliding-mode controller is robust in the face of parametric and dynamic uncertainties. The proposed controller is compared with two recent multivariable and decentralized methods. The simulation results demonstrate the advantages of the proposed controller in terms of fast and precise convergence and robust performance in face of disturbances and uncertainties.

This paper presents a simulation environment and daylighting control strategy to achieve energy-efficient lighting while providing desired lighting levels at the target points. The lighting strategy is based on a self-tuning multivariable controller, which maintains the illuminance levels at user-defined set-points while improving the energy consumption due to artificial lighting. The simulation environment utilizes the so-called layered lighting design, which allows one to evaluate the performance of different control strategies. Furthermore, the environment can be used to validate the performance of a lighting control strategy, in quasi-real-time, and assess its potential energy savings. The above approach has not been investigated in prior literature and may thus be of interest in energy-aware automated lighting systems. A case study is presented for an open-plan office space exposed to variable natural light through windows and a set of individually addressable light emitting diode luminaries.

This paper presents a primary-side control structure for operating high-brightness LED (HB-LED) strings under the constant power drive technique. To this end, an inner-outer-loop control structure is presented by utilizing an ac-dc flyback converter connected to an LED string. The proposed control structure regulates the LED power along with input current control. The input voltage and the duty cycle of flyback switch are utilized to estimate the LED power without any need to measurements from the flyback secondary or auxiliary sides. In the power control loop, the amplitude of the input current is calculated through which the LED power can be regulated. This amplitude is utilized as the amplitude of the desired input current for input current control loop, resulting in a high power factor. Experimental results are presented for delivering 20W to Cree CR22-32L LED string using the proposed power estimation and control techniques.

Power maximization is of great interest in energy conversion systems including renewable sources and alternators used in automotive systems. This paper presents a multi-surface sliding-mode extremum seeking controller for achieving Maximum Power Point Tracking (MPPT) for energy conversion involving a Lundell alternator. The proposed multi-surface sliding scheme results in smooth and fast convergence to the extremum point while achieving robust performance in face of parametric uncertainties in the alternator model. In particular, it is shown that using multiple sliding surfaces would help to reduce chattering and increase the performance speed and precision of the system. The behavior of the system in terms of convergence characteristics is analyzed using a Lyapunov-like stability analysis. Simulation results demonstrate the efficiency of the proposed controller in terms of power maximization, robustness, and convergence speed.

In this paper, a new switched-mode bidirectional bridgeless AC/DC converter, operating in the discontinuous conduction mode (DCM), for automotive energy harvesting is presented. The simple topology consisting of common source n-MOSFETs allows for direct AC/DC conversion, minimum auxiliary circuits and simple gating patterns, when compared to other AC/DC converters proposed in the literatures. The circuit operation is analyzed and shown that the converter-battery topology can operate as a synthesized variable resistor with regenerative functionality. The circuit is designed for low-power energy harvesting applications; for example, regenerating dissipated power in a vehicle suspension damper by converting vibrational energy into battery charge. Simulation results including various switching waveforms and power conversion efficiency are presented to demonstrate performance of the proposed converter. Experimental results, including power conversion efficiency and resistance synthesis sweep, by connecting the proposed converter to a regenerative vehicle suspension prototype are also included.

In this work, an adaptive control of a three phase ac/dc converter is investigated. The classical vector control method has been extensively used for the control of the ac/dc converter in different applications but the design gains are highly dependent on the system parameters. We employed an adaptive PI control method to cope with the system uncertainties. The method relies on a third order model of the converter. The simulation results confirm the good performance of the adaptive method in comparison with the established vector control method for dc voltage regulation and power factor correction.

A self-tunning adaptive control scheme for application to Switched Reluctance (SR) Motors is investigated in this work. The control gains of the proposed Pi-based control scheme are functions of the motor current and speed error signals. A second order nonlinear model of an SR Motor is considered to design the controller. The model is linearized around a nominal operation point to tune the controller. Simulation results verify the superior performance of the proposed adaptive speed control method in comparison with the conventional PI control technique. In specific, the results show that the control performance is satisfactory over a wide range of operating points.

This paper presents the development of a novel control strategy for an energy regenerative suspension mechanism. The semi-active suspension system consists of a mass-spring unit coupled with a linear permanent magnet machine and a three-phase boost converter connected to a battery. A skyhook controller is developed to provide energy transfer from the damping system to the battery. Enforcing resistive behavior across the linear machine terminals produces the same effect as controlling the mechanical damping of the suspension system. Sliding mode control approach is utilized to design the controller for the system. Numerical simulation results are presented that evaluate performance of the proposed control strategy and semi-active damping. Experimental study of the controller on a regenerative suspension system is currently under investigation.

In this paper, the development of a novel controller for a bidirectional buck and boost converter is studied to implement an active capacitance. To this end, an averaging method is used to obtain a nonlinear state-space model of the converter in the Continuous Conduction Mode (CCM) for buck and boost configurations, separately. These models are then combined into a state-space representation for the whole range of operation. Using the obtained model, a controller is designed to track a desired input current based on the applied input voltage such that the circuit exhibits a capacitive effect between the input terminals. The converter along with its proposed control method is a suitable replacement for the commonly used electrolytic capacitors in different applications. Simulation results are presented that demonstrate performance of the proposed current control method. Experimental verification is currently under investigation.

This paper proposes a mechatronic suspension system with capabilities of energy regeneration and sky- hook (SK) control incorporated into the mechanism. The system overcomes the tradeoffs between energy consumption and ride comfort in an active suspension system. Central to the concept is development of a coupled switched-mode rectifier (SMR) capable of providing either a positive or negative damping ratio by alternating between regenerative and motoring modes. Using the proposed circuit, an active sky-hook control strategy is utilized to offer continuous damping force that improves the vibration isolation significantly. Simulation results presented demonstrate the directions of power flow in both regenerating and motoring modes to verify performance of the SMR.

Control of the natural resonance frequency of an RF cavity is challenging due to the variations in the input frequency and the highly nonlinear dynamics involved. The drift of resonance frequency due to disturbances such as temperature variations has to be compensated using a sensor based feedback controller. Additionally, there are limited possibilities for measurement of relevant quantities such as the resonance frequency for the purpose of real-time control due to the extremely high frequencies involved. To address the control problem, this paper presents a nonlinear control scheme that relies on the measurement of reflected power. To this end, a mathematical dynamical model for the cavity is derived, based on which a feedback control scheme using the method of steepest descent is proposed. A Lyapunov stability analysis is presented for the closed-loop system. Simulations are presented to evaluate performance of the proposed controller.

This paper presents the analysis and design of a mechanism to be utilized as a regenerative shock absorber. The device consists of an algebraic screw mechanism, a planetary gearhead, and a DC rotary machine. The algebraic screw is a kinematic mechanism that converts the translational vibration motion into a reciprocating rotary motion which drives a rotary generator. The energy generated by the rotary machine is converted into the battery charge through a power electronic converter. In this study, the amount of damping provided by the shock absorber is analyzed using the dynamic analysis of a quarter car system. To this end, expressions for the input, captured, and lost power are presented in terms of the parameters of the shock absorber and road excitation profile. Simulations are carried out to study the characteristics of design in terms of converting vibration energy into rotary motion. Validation of the model is demonstrated by comparing the simulation and numerical results.

Control of the output current of a boost type DC-DC converter is challenging due to the non-minimum phase characteristic between the duty cycle input and output load current and the nonlinear dynamics involved. To address the control challenges, this paper presents a nonlinear control scheme combined with an output redefinition approach to regulate the output current of the converter operating in the continuous conduction mode (CCM). To this end, a feedback linearization controller is proposed based on an averaged model of the converter. The output redefinition concept relies on defining a new output to make the system minimum phase, or marginally minimum phase, so that a robust controller can be designed. Furthermore, control in the discontinuous conduction mode is studied and a switching scheme is presented to regulate the output current of the converter regardless of the operation mode. Numerical simulations are presented to evaluate performance of the proposed control scheme.

Maximum energy transfer from an arbitrary voltage source containing multiple frequencies is of great interest in various renewable energy systems involving irregular sources of power such as wind, and wave, in which the amplitude and frequency of the input voltage is time varying. This paper presents the development of a control algorithm for a boost converter operating in the continuous conduction mode so that it exhibits a resistive behavior from its input terminals. In particular, the model of a boost converter operating under the continuous conduction mode is utilized to obtain a relationship between the input voltage and current of the converter. Next a nonlinear feedback controller is developed that regulates the converter input resistance to a desired value. Controlling the input resistance of the converter can result in the unity power factor, and maximum power transfer to a storage system such as a battery or a DC link. Numerical simulations are presented that evaluate performance of the proposed modeling scheme and control system. Performance of the proposed controller in an experimental setting is currently under investigation, and will be presented at the conference.

In this work, a new modeling and control technique for a three-phase boost converter is presented for efficient transfer of energy from an irregular input power source to a battery storage device or a DC link. First, a novel network model of a three-phase boost converter is developed using the method of averaging. Based on the model obtained, a feedback controller is developed to regulate the three-phase input resistances of the circuit to the desired values. The circuit can be designed to provide purely active power conversion of a band-limited input voltage source to a DC load. Numerical simulations are presented that illustrate performance of the proposed modeling and feedback control scheme. Experimental studies of the proposed system are under investigation.

Field programmable gate arrays (FPGAs) are emerging as suitable platforms for implementing embedded control systems. This paper illustrates development of FPGA-based controllers by utilizing popular tools such as MATLAB/Simulink available for the design and development of control systems. As a case study, this paper presents how the tools can be utilized to develop a FPGA-based controller for a laboratory scale air levitation system.

In this paper, based on a passivity framework, admittance-type and hybrid-type delay-compensated communication channel models are introduced, which warrant different bilateral control architectures for wave-based teleoperation under time delay. We utilize wave transforms and signal filtering for passivating the delayed-communication channel and passivity/stability conditions are derived using scattering theory based on an end-to-end model of the teleoperation system rather than the communication channel alone. Contrary to a commonly held view, it is proven that the teleoperation system can remain stable when force measurement data of the master and the slave manipulators interactions with the operator and the remote environment are used. Experimental results on a soft-tissue task for a hybrid-type architecture and for round-trip delays of 60 msec and 600 msec show that using slave-side force measurements considerably enhances teleoperation transparency.

The prostate is a small exocrine gland in men responsible for production of the liquid component of the seminal fluid. In North America, prostate cancer accounts for over 300,000 new cases and 40,000 deaths each year and it is the second leading cause of cancer death in men. Low-dose Rate (LDR) brachytherapy is gaining interest as a viable treatment option for prostate cancer due to its low side effects and high benefits. The present manual approach for brachytherapy needle insertion and the inherent flexibility of the needles make it extremely difficult to achieve accurate and consistent dosimetry. In this paper, we present a new 5 degrees-of-freedom (DOF) manipulator capable of performing percutaneous needle insertion. The manipulator can perform orientation, insertion and rotation of the needle and linear motion of the plunger to drop radioactive seeds at targeted locations. The manipulator is an integral part of a system utilizing a mechanically rotated side-fire transducer to create 3D ultrasound images of the organ and utilizing 3D SLICER software to visualize those images. Experiments conducted in agar phantoms reveal an average RMS targeting error of 1.45mm at an average insertion depth of 75.78mm proving the feasibility and efficacy of the proposed robotic system for percutaneous needle insertion.

An ultrasound probe holder is designed for use in the prostate brachytherapy procedure. The holder comprises a passive-jointed stabilizer that can be used to position, manipulate and lock in place the ultrasound probe, and a tracker mechanism to provide the position and orientation of the probe in 3D space. The information obtained from the integrated stabilizer-tracker mechanism can be utilized in image-guided robot-assisted prostate brachytherapy procedures. Performance tests show that the tracker assembly can acquire the position and orientation of the ultrasound probe with an average displacement accuracy of 0.66 mm and roll, pitch and yaw angular accuracies of 0.24deg, 0.38deg and 0.19deg, respectively.

Discretization of a stabilizing continuous-time bilateral teleoperation controller for digital implementation may not necessarily lead to stable teleoperation. This paper addresses the stability of master-slave teleoperation under discrete-time bilateral control. Stability regions are determined in the form of conditions involving the sampling period, control gains including the damping introduced by the controller, and environment stiffness. Due to the tradeoff between stability and transparency in bilateral teleoperation, such stability boundaries are of particular importance when the teleoperation system has good transparency.

In this paper, the application of a piezoelectric stack actuator for vibration control in a large-scale robotic manipulator, called a macromanipulator, is studied. In this regard, mechanical design and mathematical modeling of the actuator are discussed. The structural flexibility of the macromanipulator includes deflection and torsional vibration modes. The vibration modes are detected using appropriate sensor attachments. Furthermore, a nominal transfer function matrix between the input signals to the actuators and the output voltages of the sensors is obtained. A closed-loop controller based on the obtained model is designed. Because of the presence of deflection and torsional vibration modes and model uncertainties resulting from manipulator motion, an robust controller is utilized. Experimental results are presented to validate the robustness and performance of the designed controller.

In master-slave teleoperation applications that deal with a delicate and sensitive environment, it is important to provide haptic feedback of slave/environment interactions to the user's hand as it improves task performance and teleoperation transparency (fidelity), which is the extent of telepresence of the remote environment available to the user through the master-slave system. For haptic teleoperation, in addition to a haptics-capable master interface, often one or more force sensors are also used, which warrant new bilateral control architectures while increasing the cost and the complexity of the teleoperation system. In this paper, we investigate the added benefits of using force sensors that measure hand/master and slave/environment interactions and of utilizing local feedback loops on the teleoperation transparency. We compare the two-channel and the four-channel bilateral control systems in terms of stability and transparency, and study the stability and performance robustness of the four-channel method against nonidealities that arise during bilateral control implementation, which include master-slave communication latency and changes in the environment dynamics. The next issue addressed in the paper deals with the case where the master interface is not haptics capable, but the slave is equipped with a force sensor. In the context of robotics-assisted soft-tissue surgical applications, we explore through human factors experiments whether slave/environment force measurements can be of any help with regard to improving task performance. The last problem we study is whether slave/environment force information, with and without haptic capability in the master interface, can help improve outcomes under degraded visual conditions.

In this paper, the application of a piezoelectric stack actuator for vibration control in a large-scale robotic manipulator, called the macro manipulator, is studied. The structural flexibility of the system includes deflection and torsional vibration modes. The vibration modes are detected using an appropriate sensor attachment. A nominal transfer function matrix between the input signals of the actuators and the output voltages of the sensors is obtained. A closed-loop controller based on the obtained model is designed. Because of the presence of different vibrational modes and model uncertainties resulting from manipulator motion as well as its varying payloads, an Hinfinrobust controller is utilized and experimental results are presented

In robot-assisted interventions, providing a surgeon with haptic information regarding contacts made between surgical instruments and tissue can improve task performance and reliability. In this paper, a force-reflective user interface is used with a sensorized surgical instrument to form a master-slave test-bed for studying haptic interaction in a soft-tissue endoscopic surgery environment. After modeling and parametric identification of the master and the slave, bilateral controllers are designed and teleoperation experiments involving a single degree of freedom surgical task on soft tissue (palpation) are conducted. The transparency of the teleoperator in terms of transmitting the critical task-related information to the user in the context of soft-tissue surgical applications is investigated

An actuated robot arm is designed for use as a macro manipulator that can carry, appropriately orient, precisely position and firmly "lock" in position different types of micro robots and surgical tools necessary for applications in minimally invasive therapy. The sophisticated configuration and joint structure of the arm enable it to perform and interact efficiently with the constrained and limited workspace of surgical environments. The normally locked braking system and the simple quick release joint enhance the safety features of the robot for emergencies and power shutdown. With a simple manipulation protocol, the surgeon can use the robot without undergoing any training. Robot workspace analysis indicates that all singularities are outside the operating work envelope. A performance analysis shows that the robot operates with an average displacement accuracy of 0.58 mm and a roll, pitch and yaw angular accuracies of 0.26deg, 0.26deg and 0.38deg respectively.

In this paper, the application of high control authority piezoelectric stack actuators, in short piezostack actuators, for active vibration control of long-reach robotic manipulators is studied. The idea is to include piezostack actuators in the base structure in order to strengthen its stiffness characteristics. A mechanism is designed for converting the force produced by a piezostack actuator to a bending moment. A flexible link actuated with a piezostack actuator is built and mathematically modeled. The solution of the governing partial differential equation with non-homogenous boundary conditions is obtained. A comparison between experimental frequency response of the system and its model is given. A control law using the Popov criterion is obtained and experimental results for closed-loop system are given.

Most conventional motion planning algorithms that are based on the model of the environment cannot perform well when dealing with the navigation problem for real-world mobile robots where the environment is unknown and can change dynamically. In this paper, a layered goal-oriented motion planning strategy using fuzzy logic is developed for a mobile robot navigating in an unknown environment. The information about the global goal and the long-range sensory data are used by the first layer of the planner to produce an intermediate goal, referred to as the way-point, that gives a favorable direction in terms of seeking the goal within the detected area. The second layer of the planner takes this way-point as a subgoal and, using short-range sensory data, guides the robot to reach the subgoal while avoiding collisions. The resulting path, connecting an initial point to a goal position, is similar to the path produced by the visibility graph motion planning method, but in this approach there is no assumption about the environment. Due to its simplicity and capability for real-time implementation, fuzzy logic has been used for the proposed motion planning strategy. The resulting navigation system is implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented which demonstrate the effectiveness of the proposed fuzzy navigation system.

In this paper the application of high control authority piezostack actuators (PSA) for active vibration control in flexible manipulators is studied. The idea is to incorporate the piezostack actuators into the system in order to strengthen its stiffness characteristics. In this regard a cantilever beam actuated with piezostack actuators is considered. A mechanism for converting the blocking force of the PSA to a bending moment is studied and a model for the whole system consisting of a flexible beam and B A is obtained. The simulation results show that the suggested method may open new possibilities in active vibration control of large flexible manipulator.

In this paper, friction compensation in robotic manipulators is studied. An observer based model of the friction force is utilized for the friction compensation algorithm. In order to evaluate the efficiency of this method two different manipulators with different friction characteristics are examined. A 2-DOF manipulator used for high-speed, micro-meter precision manipulation and a 4-DOF macro manipulator used for long reach positioning task are examined. These manipulators are characterized, according to compensation task classifications (Armstrong, B. et al., 1994), as high-reversal-velocity and low-reversal-velocity tracking tasks, respectively. In each case a steady-state model of friction is experimentally obtained. This model is further utilized in dynamic equations of the friction force during manipulation. It is shown that despite the different nature of the two manipulators the same method can effectively improve the speed and performance of the manipulation in both cases.

This paper presents experimental results for a nonlinear control scheme for controlling the deflection of a flexible beam using Shape Memory Alloy (SMA) actuators. These actuators possess interesting properties in terms of force generation capacity, possibility of miniaturization, and power consumption. However, their use in precision applications is hampered by undesirable characteristics such as nonlinearities, hysteresis, extreme temperature dependencies, and slow response. By taking into account the nonlinear and thermal characteristics, a control scheme based on partial feedback linearization is developed in order to regulate the forces exerted by a differential SMA actuator pair attached to a flexible beam. The regulated force corresponds to a specific position of the flexible beam; hence regulating the force results in position regulation. Furthermore, performance of the developed control scheme is tested experimentally on a laboratory testbed.

Minimally invasive surgery (MIS) is an alternative to open surgery where special instruments are inserted into the body cavity through tiny incisions in order to perform surgical procedures. In this work, some design issues in a master-slave robotic system for use in MIS are discussed. First, we discuss the design of a user interface that can be used to incorporate haptic interaction in robot-assisted MIS. Then we discuss the design of a laparoscopic end effector that meets MlS requirements and is instrumented for haptic feedback.

Distributed multi-robot systems have attracted considerable attention over the past few decades. Multiple robots performing tasks together in a cooperative manner can have a significant advantage over a single robot, especially in parts assembly and load sharing between two or more coordinated robots. Most multi-robot systems are hard real-tune systems and require real-time scheduling. Many real-time schedulers have been discussed including round-robin, earliest-deadline-first (EDF), minimum-laxity-first (MLF), least-slack-time-first (LST), etc. Unfortunately, none of these schemes provide enough support for relative task constraints and timing constraints that are commonly used in multi-robot systems. This paper gives a task-oriented scheduling method that can help guarantee the safety, reliability and time deadline of a distributed multi-robot system. Experiments show that with the proposed algorithm, both the timing constraints and relative task interdependencies can be satisfied.

Minimally invasive surgery involves inserting special instruments into the body cavity through tiny incisions in order to perform surgical procedures. In this paper, the design of a robotic master-slave system for use in minimally invasive surgery is discussed. This system is capable of providing haptic feedback to the surgeon in all available degrees of freedom. System design as well as master and slave bilateral control and communication issues are discussed.

In this paper, we first describe some "goal-unreachable" problems found in fuzzy logic-based algorithms for mobile robot navigation systems. Then, a new algorithm is developed to solve one of the problems, i.e., a problem with nearby obstacles. The resulting navigation system has been implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented which demonstrate the effectiveness and improvement of the resulting fuzzy navigation system over conventional fuzzy-logic navigation algorithms.

Internet-based telerobotic systems have been evolving rapidly in recent years. Using Web-based technology, telerobotic systems have been shown to have an increasing potential for a variety of applications including remote control, manufacturing, surgery, training, and education. In this paper, we present an Internet-based distributed, multiple-telerobot system that enables operators to use remote robots in order to perform cooperative tasks. Several multiple-telerobot demonstration programs have been designed, including a single telerobot training program, a multiple-telerobot "group object-handling" program, and pairs of telerobots serving Internet participants playing with a Rubik's Cube to illustrate Internet-based interaction and collaboration. Experimental tests have been performed on three demonstration programs that are presented in this paper.

This paper discusses the selection process for piezoelectric transducers (PZT) used as actuator elements for suppressing vibrations in a flexible beam system. The effects of changing physical parameters such as the relative thickness of the piezoelectric ceramic with respect to the beam, the optimum location of the PZT actuator, and the length of the PZT are studied based on the singular value decomposition of the controllability Grammian of the resulting system. A model for a clamped-mass cantilevered beam is developed and its frequency response is compared with that obtained experimentally. Simulation results are given to illustrate how this method can be used to determine physical properties and location of the PZT actuator. Further experimental studies are currently being performed.

The basic idea of RISC (reduced intricacy sensing and control) robotics is an attempt to perform challenging industrial manufacturing tasks by using a combination of simple hardware and sophisticated algorithms. Many effective strategies and algorithms have been explored. However, the issue of optimal design of RISC sensor has not been solved. The main reason is the shortage of good models. In this paper, we propose a statistical model for one of the typical RISC sensors, i.e. the crossbeam sensor. Based on this statistical model we employ the multiple hypotheses-testing method as optimal design technique and present its applied strategies. It is believed that this work will lead to development of new RISC sensors because a new principle and a pertinent model are introduced into this area.

We present a control scheme for high-speed vibration-free positioning of a system consisting of a rigid manipulator mounted on a flexible base. The objective is to move the end-point of this macro-micro manipulator system rapidly by proper motion of the micro-manipulator and without inducing structural vibrations when the joints of the flexible macro-manipulator are locked. It is shown by an example that the system is in general non-minimum phase. A control strategy is developed for rapid positioning of the end-effector of the micro-manipulator that will achieve the above goal. Simulation results are presented for a two-link manipulator mounted on a flexible boom.

This paper focuses on the experimental implementation of an observer-based decoupling control strategy for tip-position tracking of a class of multilink flexible manipulators. The control strategy is based on output redefinition and input-output decoupling that was studied by the authors in an earlier paper. Since the rates of change of flexible modes are required, a nonlinear observer is implemented to estimate these variables. Experimental results are given for the case of a two-link flexible manipulator that further confirm the theoretical and simulation results. The closed-loop performance under different observation schemes is evaluated and compared to the case when conventional methods are used.

In this paper, a nonlinear control strategy for tip position trajectory tracking of a class of structurally flexible multilink manipulators is developed. Using the concept of integral manifolds and singular perturbation theory, the full-order flexible system is decomposed into corrected slow and fast subsystems. The tip-position vector is similarly partitioned into corrected slow and fast outputs. To ensure an asymptotic tracking capability, the corrected slow subsystem is augmented by a dynamical controller in such a way that the resulting closed-loop zero dynamics are linear and asymptotically stable. The tracking problem is then redefined as tracking the slow output and stabilizing the corrected fast subsystem by using dynamic output feedback. Consequently, it is possible to show that the tip position tracking errors converge to a residual set of O(/spl epsiv//sup 2/), where /spl epsiv/ is the singular perturbation parameter. A major advantage of the proposed strategy is that the only measurements required are the tip positions, joint positions, and joint velocities. Experimental results for a single-link arm are also presented and compared with the case when the slow control is designed based on the rigid-body model of the manipulator.

In this paper, an index of optimization is proposed for improving the dynamic behavior of structurally flexible manipulators. The improvement is achieved through an optimization scheme where a cost function associated with the lowest natural flexible mode and an index defined as modal accessibility, is optimized subject to certain constraints. The formulation assumes a singularly perturbed model of the flexible-link system as this system possesses two-time scale properties. To illustrate the approach, the design of a two-link, non-uniform, planar, flexible manipulator is considered which results in improved performance characteristics as compared to a uniform manipulator.

In this paper a nonlinear control strategy for tip position trajectory tracking of a class of structurally flexible multi-link manipulators is developed. Using the concept of integral manifolds and singular perturbation theory, the full-order flexible system is decomposed into corrected slow and fast subsystems. The tip position vector is similarly partitioned into corrected slow and fast outputs. To ensure an asymptotic tracking capability, the corrected slow subsystem is augmented by a dynamical controller in such a way that the resulting closed-loop zero-dynamics are linear and asymptotically stable. The tracking problem is then re-defined as tracking the slow output and stabilizing the corrected fast subsystem by using dynamic output feedback. A major advantage of the proposed strategy is that the only measurements required are the tip positions, joint positions, and joint velocities.