Research on third-harmonic injection based on nonlinear active disturbance rejection

Recurrent modified Elman neural network control of PM synchronous generator system using wind turbine emulator of PM synchronous servo motor drive

AC permanent magnet synchronous motor servo control system is a complex nonlinear, strong coupling and time-varying system. It has strong uncertainty and nonlinearity, and when the system is running, it also will be disturbed to varying degrees, so the conventional control strategy is difficult to meet the control requirements of high accuracy, high speed and high-performance servo system. This paper adopts a direct feedback linearisation control strategy based on sensor technology and uses, as the output of the system to realise the decoupling of the system. In addition, the grey prediction is added to overcome the shortcomings of direct feedback linearisation that is sensitive to parameters. Adjusting the uncertain factors block by grey prediction to adapt to the direct feedback linearisation rule and achieve the desired effect. MATLAB/Simulink is used to complete the simulation of servo control algorithm. The simulation results show that the direct feedback linearisation control is better than the conventional PID control, and the direct feedback linearisation control algorithm with grey prediction can improve the performance of the permanent magnet synchronous motor servo control system and can meet the basic requirements of the high-performance servo control system.

In this article, an improved hybrid particle swarm optimization (IHPSO) algorithm is proposed to solve the optimization problem of controller parameters in the design of a permanent magnet synchronous motor (PMSM) servo system. The proposed algorithm presents the directional mutation operation to the particles, which fixes the position of some particular particles so as to enhance the searching ability to some remote regions. In order to cooperate with directional mutation operation, the updating formula of particles velocity is ulteriorly improved. Then, the proposed IHPSO algorithm is adopted to optimize parameters of the designed controller. A simulation and an experimental platform of the PMSM servo system are designed using a biological intelligence controller based on hormone regulation for the speed control and feedforward compensation for the position controller, where IHPSO is applied to the parameter optimization for speed and position controllers, which validate the effectiveness of the IHPSO algorithm and the designed control system.

Permanent magnet synchronous motor (PMSM) servo system requires a high dynamic performance of speed. The control object of speed loop, which can be described using a two-order transfer function, is the PMSM regulated by current loop. PI controller is generally used in speed control, in which the performance improvement is limited by the strong coupling and nonlinearity of the system. In this paper, an adaptive model following speed controller (AMFC) with state feedback control and model following methods is designed based on the Popov hyperstability theory and modeled in the MATLAB. The simulation results show that, compared with PI control, AMFC raises the speed loop dynamic performance of PMSM by compensating the influence of coupling and nonlinearity, so it is more suitable for servo system.

Permanent magnetic synchronous motor (PMSM) is a strong coupling and non-linear system. In the speed-loop of PMSM servo system controlled by active disturbance rejection controller (ADRC), it is difficult to ensure the estimation precision of disturbance by extended state observer (ESO) in the case of big disturbance. In the paper, the ADRC based on the artificial neural network (ANN) is applied to the speed-loop of PMSM servo system. The result of simulation shows that this algorithm has better anti-load-disturbance performance.

Super-twisting sliding mode control (STM) offers advantages such as fast response and low demand on motor model accuracy, and is attractive for the permanent magnet synchronous motor (PMSM) servo systems. However, the inherent chattering issue and limited disturbance rejection capability degrade its servo control performance. To overcome these limitations, this paper proposes an improved STM approach using a variable reaching law super-twisting sliding mode (VRSTM) strategy, integrating a high-order disturbance observer (HODOB) to estimate all perturbations including motor parameter mismatch, to achieve a high-precision speed control for the servo systems. Compared to the conventional reaching law, the proposed VRSTM accelerates convergence during trajectory deviations from the sliding surface while decelerating near the surface, hence achieving a better dynamic response performance and chattering mitigation. Furthermore, by implementing the HODOB, the perturbations including motor parametric variations are estimated to enhance the disturbance rejection capability of the proposed VRSTM approach. Theoretical analysis confirms the validity of the proposed method in improving the dynamic performance, suppressing chattering phenomena, and enhancing disturbance rejection capabilities for PMSM servo drives. Simulation and experimental results confirm the effectiveness and robustness of the proposed method.

The objective of this paper is to control the speed of Permanent Magnet Synchronous Motor (PMSM) over wide range of speed by consuming minimum time and low cost. Therefore, comparative performance analysis of PMSM on basis of speed regulation has been done in this study. Comparison of two control strategies i.e. Field oriented control (FOC) without sensor less Model Reference Adaptive System (MRAS) and FOC with sensor less MRAS has been carried out. Sensor less speed control of PMSM is achieved by using estimated speed deviation as feedback signal for the PI controller. Performance of the both control strategies has been evaluated in in MATLAB Simulink software. Simulation studies show the response of PMSM speed during various conditions of load and speed variations. Obtained results reveal that the proposed MRAS technique can effectively estimate the speed of rotor with high exactness and torque response is significantly quick as compared to the system without MRAS control system.

Nonlinear active disturbance rejection control is much more effective than linear active disturbance rejection control in tolerance to uncertainties and disturbances. However, it brings a great challenge for theoretical analysis, especially the stability analysis. This article proposes a linear matrix inequality method to analyze the absolute stability of generalized nonlinear active disturbance rejection control form which contains multiple nonlinearities with different parameters in both extended state observer and control law for single-input single-output systems. The generalized nonlinear active disturbance rejection control algorithm and the single-input single-output system are transformed into a direct multiple-input multiple-output Lurie system. A sufficient condition to determine its absolute stability based on linear matrix inequality method is given. The Lyapunov function of the Lurie system exists when the group of linear matrix inequalities is feasible. The free parameters and coefficients in Lyapunov function are given by the solution of these linear matrix inequalities. The electromagnetic valve actuator system in camless engine is presented as an application to illustrate how to perform the proposed method for absolute stability analysis and the stable region of parameter perturbations is obtained via the method. Simulation results show that the linear matrix inequality–based method is convenient and effective to determine whether the closed-loop system is absolutely stable.

High dynamic response has always been one of the goals of the surface-mounted permanent magnet synchronous motor (SPMSM) servo system. To this end, this article proposes an anti-disturbance enhanced finite-time composite control strategy for the SPMSM servo system. First, a finite-time controller is designed to enhance the rapidity of the SPMSM speed loop. Second, an anti-disturbance enhanced finite-time disturbance observer is proposed, which optimizes the disturbance compensation channel and accelerates the disturbance compensation rate. Meanwhile, this method decouples the parameters of the controller and disturbance observer, making it easier to tune the parameters. Finally, combining the controller with the disturbance observer, the proposed composite control scheme has better dynamic performance than the traditional finite-time composite controller. The experimental evaluation results verify the superiority of the proposed method.

Permanent magnet (PM) synchronous motors (PMSMs) have been used to drive a number of vehicles. They have high torque density, high efficiency, and a wide speed range. However, the high cost of PMs is disadvantageous. This paper presents a technique for increasing the torque density by modifying the shape of the PMs and minimizing the magnet volume. The PM characteristics such as flux density, demagnetizing force, PM energy product, and the air-gap flux density are represented by a lumped magnetic equivalent circuit when the thickness and width of the PM are increased for the same volume but with different shapes. The torque, torque ripple, core loss, magnet loss, and efficiency of three interior (IPMSM) models designed by the proposed method are compared by finite element analysis. In addition, the demagnetization of the PM due to high temperature, maximum torque load angle, and an adverse field is analyzed. Finally, the analysis result is compared with that of the experiment to verify the proposed model.

In this paper, a novel nonlinear active disturbance rejection (ADR) controller is proposed for the speed control of electric drives so that a better robustness to parameter variations can be achieved. The nonlinear observer is designed by using the sliding mode techniques. When the nonlinear observer is simplified as a linear one, it is equivalent to a phase-locked loop observer (PLLO). However, compared with the existing PLLO, the proposed observer has two gains with specific physical interpretation, which simplifies the gain tuning process, especially for the nonlinear observer. To alleviate the chattering problem, the fraction power function is employed in the observer and the guideline for parameter setting is present. An experimental comparative study of the linear PLLO and the proposed nonlinear PLLO is provided to show the effectiveness.

This paper examines the enhancement of Electric Vehicle (EV) Permanent Magnet Synchronous Motor (PMSM) drives through the integration of Field-Oriented Control (FOC) with Model Predictive Control (MPC). The study aims to achieve high precision and dynamic response for PMSM drives under diverse operating conditions. FOC provides good control capability over full torque and speed ranges. MPC is an optimal control technique in which the calculated control actions minimize a cost function for a constrained dynamic system. The theoretical framework combines FOC and MPC principles, utilizing MPC's predictive capabilities to optimize d-q current references in real-time. The methodology encompasses the design and implementation of an MPC technique integrated with FOC, with key objectives including minimising torque ripples, maintaining vehicle stability through robust control loops, and optimising PMSM drive performance across a wide speed range of EV. Different types of torque control methodologies, such as PI Controller and Voltage Vector Control for PMSM Control, can be applied to an electric vehicle. The results indicate significant improvements in torque ripple reduction, dynamic response, and disturbance rejection, demonstrating the robustness and adaptability of the proposed control system compared with the PI Controller. This approach effectively addresses key challenges and signifies advancements over traditional control methods, contributing to the field of electric vehicle control systems.

This chapter describes the sliding-mode control of permanent magnet synchronous motor (PMSM) servo systems. The typical structure of the systems consists of the position, velocity, and current control loops. The design of three controllers, position controller, speed controller, and current controller, and a filter in speed loop has been described respectively, aimed at reaching high-performances of PMSM servo systems, such as fast response, strong robustness, and high precision. The digitization of terminal sliding-mode (TSM) controllers of PMSM servo system has been discussed for the purpose of practical implementation.

Background: The conventional method using one-degree-of-freedom (1DOF) controller for Permanent Magnet Synchronous Motor (PMSM) servo system has the trade-off problem between the dynamic performance and the robustness. Methods: In this paper, by using H∞ control theory, a novel robust two-degree-of-freedom (2DOF) controller has been proposed to improve the position control performance of PMSM servo system. Using robust control theory and 2DOF control theory, a H∞ robust position controller has been designed and discussed in detail. Results: The trade-off problem between the dynamic performance and robustness which exists in one-degree-of-freedom (1DOF) control can be dealt with by the application of 2DOF control theory. Then, through H∞ control theory, the design of robust position controller can be translated to H∞ robust standard design problem. Moreover, the control system with robust controller has been proved to be stable. Conclusion: Further simulation results demonstrate that compared with the conventional PID control, the designed control system has better robustness and attenuation to the disturbance of load impact.

Periodic adaptive learning control of PMSM servo system with LuGre model-based friction compensation