On Digitization of Variable Structure Control for Permanent Magnet Synchronous Motors

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.

In order to implement the speed control and improve the robustness of permanent magnet synchronous motor (PMSM) servo systems associated with the sliding-mode control (SMC), a compact integrated SMC controller designed for position servo systems is proposed in this paper. The merits of the SMC approach and PID control are combined to design this novel integrated controller. Some integral and feedforward compensatory strategies are also applied to eliminate chattering induced by traditional variable structure control. Both simulations and experimental results demonstrate the validity of the new method and the feasibility of the control strategies.

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.

An adaptive model-output-following controller using a variable structure system (VSS) approach is proposed in this paper. Only output from the plant is needed in the VSS control law to enhance the robustness of the control system. The position control of a permanent magnet (PM) synchronous motor servo drive using the proposed control strategy is illustrated. First, an integral-proportional (IP) position controller is systematically designed according to the prescribed drive specifications of the command tracking. Next, in order to allow the given specifications to be maintained under wide operating conditions, the state-space model of the systematically designed inner IP speed loop in the nominal case is chosen as the reference model. Then, the proposed adaptive controller based on VSS theory is designed and augmented to the inner speed loop to preserve the control performance. Simulation results show that the proposed control approach results accurately model the following characteristic and is robust with regard to plant parameter variations and external load disturbance.

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.

In order to improve the anti-disturbance performance of permanent magnet synchronous motor (PMSM) servo system, a sliding-mode control strategy using a new reaching law (NRL) is proposed. The NRL incorporates power term and switching gain term of the system state variables into the conventional exponential reaching law (CERL), which can effectively suppress the sliding-mode chattering and increase the convergence rate of system state reaching sliding-mode surface. Based on this new reaching law, a sliding-mode speed controller (SMSC) of PMSM is designed. At the same time, to solve the chattering problem caused by the large sliding-mode switching gain, an anti-disturbance sliding-mode speed controller method with an extended sliding-mode disturbance observer (ESMDO), called SMSC+ESMDO method, is developed. The sliding-mode disturbance observer is designed to accurately estimate the motor speed and external load disturbances, and the disturbance estimator is used as a feed-forward to compensate the sliding-mode speed controller (SMSC) to improve the system robustness and reduce the system chattering. Simulation and experimental results show that the proposed compound sliding-mode control strategy can effectively improve the dynamic performance and robustness of the system compared with the PI controller.

Based on the finite-time control technique, the position control problem of permanent magnet synchronous motor(PMSM) servo system is studied. Using backing-stepping method, a control scheme based on feedback linearization and finite-time control technique is proposed for position loop. Rigorous mathematical analysis is given for the close loop system performance in the presence of disturbances. The results show that, compared with the conventional control scheme based on PD and feedback linearization, this method not only makes the position tracking error of the closed loop system with a faster convergence rate, but also makes the boundary of steady-state error smaller by regulating the controller parameters, which means the closed loop system has stronger disturbance rejection property. The simulation results validate the efficiency of this method.

This article presented an improved nonlinear sliding mode control based on disturbance observer for the permanent magnet synchronous motor servo system. The position transient response performances, such as fast response and non-overshoot, are enhanced by the introduction of novel nonlinear sliding surface in the design of sliding mode control law. In order to abolish the analysis necessity of changeable uncertainties and alleviate the system chattering, the nonlinear sliding mode control algorithm is improved by adaptive parameter estimation and saturation function. Since the improved nonlinear sliding mode control algorithm is sensitive to mismatched uncertainties which are mainly due to the load disturbance, a disturbance observer is put forward to estimate the mismatched uncertainties and is integrated into control law design to improve the positioning accuracy. The stability of improved nonlinear sliding mode control based on disturbance observer is proved based on the Lyapunov approach. The simulation results demonstrate the effectiveness and robustness of the proposed improved nonlinear sliding mode control based on disturbance observer for permanent magnet synchronous motor servo system with stationary and dynamic trajectory tracking.

A novel on-line self-tuning of PI speed controller is given for AC servo drive. Based on iterative learning control (ILC), the proposed scheme has solved the problem of uncertain input-output relationship. Like artificial operation, the proposed scheme can improve its control quality according to historical control experience. The feasibility and validity of the method has been proved on permanent magnet synchronous motor (PMSM) servo system

Because an electric scooter driven by permanent magnet synchronous motor (PMSM) servo system has the unknown nonlinearity and the time-varying characteristics, its accurate dynamic model is difficult to establish for the design of the linear controller in whole system. In order to conquer this difficulty and raise robustness, a novel adaptive recurrent Legendre neural network (NN) control system, which has fast convergence and provide high accuracy, is proposed to control for PMSM servo-drive electric scooter under external torque disturbance in this study. The novel adaptive recurrent Legendre NN control system consists of a recurrent Legendre NN control with adaptation law and a remunerated control with estimation law. In addition, the online parameter tuning methodology of the recurrent Legendre NN control and the estimation law of the remunerated control can be derived by using the Lyapunov stability theorem. Finally, comparative studies are demonstrated by experimental results in order to show the effectiveness of the proposed control scheme.

This paper compares common PI controller with proximate time-optimal servomechanism (PTOS), composite nonlinear feedback (CNF) control law, and a mode switching control (MSC) scheme. The structure of PI controller is simple and easy to implement. The PTOS control law devotes to fast acceleration and deceleration, while the CNF control law consists of a linear feedback part for achieving fast response and a nonlinear feedback part for suppressing the overshoot caused by the linear part, so as to improve the transient performance in set-point tracking. The MSC scheme is proposed to achieve fast and precise set-point tracking in servo systems. The control scheme incorporates a CNF control law into PTOS control. These control laws were then applied to the position-velocity control loop in a permanent magnet synchronous motor (PMSM) servo system in simulation. The simulation results verify that the PTOS control is capable of tracking the target position fast, the CNF control can achieve the target position with a small overshoot and under the MSC scheme the servo system is able to track a wide range of target positions fast and accurately.

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

This paper proposes a parameter tuning method of fractional-order active disturbance rejection controller (FOADRC) for permanent magnet synchronous motor (PMSM) servo system with frequency-domain analysis. In this method, a fractional-order proportional derivative (FOPD) and a fractional-order [proportional derivative] (FO[PD]) controllers design combining with active disturbance rejection control (ADRC) are proposed. A systematic parameter tuning scheme is presented, and a flat phase constraint is applied as a design specification, which guarantees the phase is flat around the gain crossover frequency point. The closed-loop system is robust to gain variations. The simulation results illustrate that the response of the PMSM servo system using FO[PD]-ADRC has a smaller overshoot, less tracking error, and better resistance to load disturbance than that using fractional-order proportional derivative ADRC (FOPD-ADRC).

An important function of the steer-by-wire (SBW) system is to follow a desired steering angle accurately. However, it is impossible to avoid transmission backlash in the servo system, which will aggravate the mechanical vibration and cause delays and fluctuations in control system responses. A composite controller for permanent magnet synchronous motor (PMSM) servo system is proposed in this paper to solve the adverse effects resulting from backlash of the SBW system. To mitigate the effects of backlash nonlinearity, the dead-zone backlash model is identified utilizing the particle swarm optimization (PSO) algorithm, and its influence is compensated in the controller. Additionally, to address the model declination and unpredictable disturbances, a nonsingular fast terminal sliding mode controller (NFTSMC) combined with a super-twisting extended state observer (STESO) is designed. In simulation experiments, a SBW control system model is built to evaluate the performance of the disturbance observer and the angle following controller. In hardware-in-loop (HIL) experiments, the angle tracking control capability of the novel method is further evaluated under the double lane change condition. Finally, the results of simulation and HIL experiments are offered to validate the excellence of the novel method.