This paper is concerned with the problem of robustly estimating the speed and acceleration of servo drives without the system model parameter information, depending on only the order of the open-loop system. The proposed filtering solution incorporates the disturbance observer (DOB) into the second-order pole-zero cancellation (PZC) observer. The main contributions fall into three parts. First, the model-free Luenberger observer as the first subsystem specifies its gain structure in the nonlinear form to invoke the second-order PZC. Second, the first-order nonlinear DOB as the second subsystem estimates the high-frequency disturbance to yield the compensation term for the second-order PZC observer. Third, the combination of these two subsystems eventually results in the diagonalized estimation error dynamics, which makes the performance adjusting process more convenient for field engineers. The experimental study confirms the effectiveness of the proposed filtering solution using a 500-W brushless DC (direct current) motor-based servo drive under various operation modes.

This article addresses the filtering of position, speed, and acceleration in servo motor applications by confronting practical challenges such as model dependence, complex matrix computations, and inconsistent performance. The proposed filter is systematically derived through the integration of a disturbance observer (DOB) design and a high-order pole–zero cancellation (PZC) technique, yielding the following contributions. First, a double-integral, offset-free position filter reduces the order of the filtering error dynamics by employing nonlinearly parameterized gains. Second, the combination of the DOB-based system with these gains facilitates the design of speed and acceleration filters based on filtered position measurements. Third, the diagonalization of the filtering error dynamics via nonlinear gain parameterization simplifies the tuning process for desired performance. The experimental validation using a 500-W brushless dc motor-based dynamometer demonstrates a 27% improvement in feedback system performance compared to a well-tuned extended state observer (ESO).

The proposed cascade-type feedback system stabilizes the terminal voltage of single machine infinite bus (SMIB) systems using two measurements: power angle and terminal voltage. The resultant control law only requires the nominal system parameters of the SMIB, and the observer removes any model dependence. This paper provides several contributions. First, the high-order pole-zero cancellation (PZC) technique constructs the observer to estimate the time derivatives of the terminal voltage and power angle measurements without any SMIB model information. Second, the high-order PZC technique enables the outer loop to estimate the desired power angle reference along the critically damped dynamics for the terminal voltage. Third, the observer-based proportional-double integral-derivative control law for the inner loop exponentially stabilizes the power angle error by reducing the closed-loop order to 2 through the high-order PZC technique. A MATLAB/Simulink implementation of the proposed cascade-type feedback system validates the effectiveness of the proposed solution.

This paper presents a novel filtering solution for servo system applications to extract the speed and acceleration information from the imperfect angle measurement. The proposed solution forms a cascade-type structure without using plant information, including its structural and parameter information, with the following contributions: (a) an improved disturbance attenuation capability incorporating the nonlinearly structured filter gain into the extended state observer and (b) a simple performance tuning process that does not involve matrix algebra to determine the desired filtering gain due to the filtering error dynamics diagonalization by the pole-zero cancellation technique. Moreover, the closed-loop filtering dynamics are rigorously analyzed, and various experiments validate the feasibility of the proposed solution.

This article exhibits a current controller guaranteeing the performance recovery property despite the parameter uncertainties for interior-mounted permanent magnet synchronous motors (IPMSMs). The contributions of the proposed method are as follows. The first one is to build the current control law for the closed-loop system to asymptotically recover the target current tracking performance, while estimating the unknown parameters. The second one is to present a systematic way assigning the optimal control gains by solving an optimization problem. The third one is to rigorously analyze the internal dynamics problem caused by the speed dynamics of IPMSMs. The efficacy of the proposed method is verified by conducting experiments where the proposed method is applied to a 5-kW IPMSM.

IEC61131-3 is an international standard related to programming languages used to develop PLC control systems. This paper introduces a system that can verify and validate a process automation program developed in compliance with IEC61131-3 using a 3D simulator. Robot driven commands and codes related to object manipulation communicate with Gazebo-ROS system to verify the automation program. To this end, the PLC controller and Gazebo-ROS exchange data using TCP/IP communication protocol and ROS nodes and Linux threads are developed to translate ROS-type messages into PLC controller messages. Gazebo-ROS integrated software architecture is developed after designing the task allocation algorithms using the IEC61131-3 language to verify the developed PLC program. In particular, the task allocation algorithms consist of three static algorithms, each of which is used for a specific scenario, and one dynamic algorithm that interchanges between the three static algorithms given some variation in the task scenarios.