The negative impedance caused by constant power load (CPL) may lead to the instability of overall power system. In this article, the regulation problem of output voltage of dc-dc converters subject to unknown CPLs is addressed. Our main contribution in this article is to design an adaptive energy shaping control (ESC) algorithm, which combines passivity theory with immersion and invariance technology, to stabilize dc-dc buck converter and boost converter with CPLs, respectively. Three good features of the proposed control method are that (1) the stability analysis and controller design are based on large signal model, (2) the proposed control scheme is implemented without needing the knowledge of power load, and (3) the estimation of domain of attraction is presented to guarantee strictly the asymptotic convergence of closed-loop system. The performance of the proposed controller is assessed via detailed simulation and experimental results.

In this paper, we address the problem of stabilisation of robots subject to nonholonommic constraints and external disturbances using port-Hamiltonian theory and smooth time-invariant control laws. This should be contrasted with the commonly used switched or time-varying laws. We propose a control design that provides asymptotic stability of an manifold (also called relative equilibria)-due to the Brockett condition this is the only type of stabilisation possible using smooth time-invariant control laws. The equilibrium manifold can be shaped to certain extent to satisfy specific control objectives. The proposed control law also incorporates integral action, and thus the closed-loop system is robust to unknown constant disturbances. A key step in the proposed design is a change of coordinates not only in the momentum, but also in the position vector, which differs from coordinate transformations previously proposed in the literature for the control of nonholonomic systems. The theoretical properties of the control law are verified via numerical simulation based on a robotic ground vehicle model with differential traction wheels and non co-axial centre of mass and point of contact.

Well known as an efficient and eco-friendly power source, fuel cell, unfortunately, offers slow dynamics. When attached as primary energy source in a vehicle, fuel cell would not be able to respond to abrupt load variations. Supplementing battery and/or supercapacitor to the system will provide a solution to this shortcoming. On the other hand, a current regulation that is vital for lengthening time span of the energy storage system is needed. This can be accomplished by keeping fuel cell's and batteries' current slope in reference to certain values, as well as attaining a stable dc output voltage. For that purpose, a feedback control system for regulating the hybrid of fuel cell, batteries, and supercapacitor was constructed for this study. Output voltage of the studied hybrid power sources (HPS) was administered by assembling three dc-dc converters comprising two bidirectional converters and one boost converter. Current/voltage output of fuel cell was regulated by boost converter, whereas the bidirectional converters regulated battery and supercapacitor. Reference current for each converter was produced using Model Predictive Control (MPC) and subsequently tracked using hysteresis control. These functions were done on a controller board of a dSPACE DS1104. Subsequently, on a test bench made up from 6 V, 4.5 Ah battery and 7.5 V, 120 F supercapacitor together with a fuel cell of 50 W, 10 A, experiment was conducted. Results show that constructing a control system to restrict fuel cell's and batteries' current slope and maintaining dc bus voltage in accordance with the reference values using MPC was feasible and effectively done.

This paper presents two versions of adaptive controllers for nonlinear bilateral teleoperators, each providing asymptotic convergence of velocity and position errors to zero, independent of constant time-delays. Moreover, the proposed schemes do not rely on the use of the scattering transformation. The paper also proves that the teleoperator is Input-to-State Stable from human operator and environment inputs to some synchronization signals. Simulations show the effectiveness of the proposed controllers.

Two controllers capable of achieving asymptotic convergence of position and velocity errors, of the ith-manipulator within a multiple robot network, are proposed. The controllers employ adaptive techniques to find an estimate of the physical parameters of the nonlinear dynamics of the robot network. Moreover, the controllers can deal with different connectivity topologies (ring and star) and and can handle time-delays in the communications. Simulations, using a ten robot manipulators network with different connectivity topologies, that confirm the theoretical results are presented.

In a recent scheme, with delayed derivative action [Lee and Spong,IEEE Trans. Robot., vol. 22, no. 2, pp. 269--281, Apr. 2006], it is claimed that a simple proportional derivative (PD) scheme yields a stable operation. Unfortunately, the stability proof hinges upon unverifiable assumptions on the human and contact environment operators, namely, that they define${\cal L}_\infty$--stable mapsfrom velocity to force. In this short paper, we prove that it is indeed possible to achieve stable behavior with simple PD-like schemes---even without the delayed derivative action---under the classical assumption of passivity of the terminal operators.

This paper addresses the problem of stable bilateral teleoperation, through a time-delayed communication channel, for a n-DOF system without position drift. The classical wave variables-based scheme encodes velocity and force whilst the proposed scheme encodes position and integral of force. The resulting passive communication scheme is used in an extended teleoperation framework, in which the human operator can define geometrical motion restrictions in order to increase his awareness and his feeling of immersion, hence improving his ability to perform complex tasks. The framework also provides the operator with video feedback and 3D rendering of the remote scene.

This paper addresses the problem of steady-state position and force tracking in bilateral teleoperation. Passivity-based control schemes for bilateral teleoperation provide robust stability against network delays in the feedback loop and velocity tracking, but do not guarantee steady-state position and force tracking in general. Position drift due to data loss and offset of initial conditions is a well-known problem in such systems. In this paper, we introduce a new architecture, which builds upon the traditional passivity-based configuration by using additional position control on both the master and slave robots, to solve the steady-state position and force-tracking problem. Lyapunov stability methods are used to establish the range of the position control gains on the master and slave sides. Experimental results using a single-degree-of-freedom master/slave system are presented, showing the performance of the resulting system

A control-theoretical solution is presented for the direct adaptive visual control of planar manipulators using a fixed camera, when both camera calibration and robot dynamics are uncertain. The proposed scheme is developed for image-based look-and-move visual systems to allow tracking of a moving target. In order to solve the multivariable parameter adaptive problem, the proposed immersion and invariance (I&I) method is used. The scheme is then combined with the adaptive controller for the manipulator, taking into account its nonlinear dynamics and leading to an overall stable adaptive visual system. Simulations and experimental results are also presented for the proposed strategy.

We present two globally convergent vision-based position controllers for a planar two-links manipulator in the so-called fixed-camera configuration, where the camera orientation and scale factor are considered unknown. This is a basic adaptive visual servoing problem whose solution was hampered by the nonlinear dependence of the system dynamics on the unknown parameters. The controller design techniques of immersion and invariance and nonlinear proportional integral (PI) are used to derive the smooth adaptive schemes that ensure global asymptotic regulation without overparameterization, projections, or persistency of excitation assumptions. In the case of tracking, we establish error bounds that are reduced, eventually to zero, as the speed of the reference trajectory decreases, and with improved prior knowledge on the camera scale factor, for the immersion and invariance controller, or increasing a tuning gain for the nonlinear PI. The efficacy of the approaches is shown through simulations.

We address, and solve, a basic adaptive visual servoing problem whose solution was hampered by the nonlinear dependence of the system dynamics on the unknown parameters. Namely, we present a globally convergent vision-based position controller for a planar two-links manipulator in the so-called fixed-camera configuration, where the camera orientation and scale factor are considered unknown. The controller design technique of immersion and invariance is used to derive a smooth adaptive scheme that ensures global asymptotic regulation without overparametrization, projections or persistency of excitation assumptions. In the case of tracking, we establish error bounds that depend on the speed of the reference trajectory, and can be reduced (eventually to zero) with improved prior knowledge on the camera scale factor. The efficacy of the approach is shown through simulations.

In this paper we characterize a class of passivity-based regulators for robot manipulators which, without assuming velocity measurement, aims at modifying the total energy of the closed loop and adding the required dissipation. The class is parametrized in terms of the desired closed loop total energy function, specified by the designer. We show that several apparently unrelated stabilizing output feedback regulators recently reported in the literature, are in fact particular cases of this class. Our results aim at providing a unified framework to compare different stabilizing schemes via analysis of their energy dissipation properties.>

A globally convergent adaptive control scheme for robot motion control with the following features is proposed. First, the adaptation law possesses enhanced robustness with respect to noisy velocity measurements. Second, the controller does not require the inclusion of high gain loops that may excite the unmodeled dynamics and amplify the noise level. Third, we derive for the unknown parameter design a relationship between compensator gains and closed-loop convergence rates that is independent of the robot task. A simulation example of a two-DOF manipulator featuring some aspects of the control scheme is given.>

The authors propose a globally convergent adaptive control scheme for robot motion control with the following features: first, the adaptation law processes enhanced robustness with respect to noisy velocity measurements; secondly, the controller does not require the inclusion of high-gain loops that may excite the unmodeled dynamics and amplify the noise level; thirdly the authors derive for the known parameter design a relationship between compensator gains and closed-loop convergence rates which is independent of the robot task. This helps the designer to carry out the gain tuning with an analysis of the robustness-performance tradeoff.>

Impedance control specifications for robot manipulators are given in terms of a desired motion trajectory and a desired dynamic relationship between position errors and interaction forces. An adaptive implementation is proposed as an alternative to reduce the design sensitivity due to model-manipulator parameter mismatch. Two adaptive controllers that globally achieve the impedance objective for the general nonlinear dynamic model are presented. The controller structures consist of a nonlinear feedback of positions, velocities, and end-effector applied forces. Computer simulations were carried out to demonstrate stability and performance control.>

The stability of adaptive controllers for robot manipulators using an input-output approach is studied. A recently proposed adaptive controller is analyzed in this functional analytic framework. Global stability results are presented. The input-output approach provides a framework for control and adaptation laws design.>

An online parameter-estimation algorithm is presented which has the following features: (1) it reduces to the linear least-squares (LS) estimator after a set of regression vectors that span the full dimension of the parameter space has been processed, and (2) when the regression model is linear in the parameters, the parameter and prediction errors converge to zero in finite time. Both continuous- and discrete-time versions of the algorithm are given.>

An algebraic formulation of the positive-real (PR) condition of transfer functions is given. It provides a simple interpretation in terms of a polynomial inequality whose computational solution may be shown to be numerically stable. A class of transfer functions which do not verify the PR condition is given in terms of the roots of these polynomials. An example of interest in adaptive control theory furnishes insight into the proposed method.