Expanded proximate time-optimal servo control for motor position regulation

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.

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 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.

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.

In the permanent magnet synchronous motor servo system, as the motor nonlinearity, strong coupling, parameters variability, and hydraulic systems nonlinear factors such as leaks, Coulomb friction and the uncertainty of the load force, output torque of the motor is interfered with the large random disturbances, and the system suffers from serious dynamic nonlinearity. Adaptive observer is adopted to carry the load torque adaptive control by the estimation error, improve the dynamic performance, and increase disturbance restraint performance. Using Lyapunov stability theory analyses convergence conditions and proves the system stability. The system simulation experiment shows that the control method has strong robustness on parameters variation and random disturbance.

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.

This article investigates the sliding mode control problem of uncertain nonlinear systems and its application in tracking periodic motion. Traditional sliding mode control fulfils perfect tracking at the cost of chattering, especially in the case of high-frequency scenarios. To address the limitations of this method, this article introduces the internal model of the reference signal in building the sliding manifold, which fully takes the advantages of two fundamental methodologies. Specifically, the internal model of the reference signal is involved in the closed-loop system dynamics after the sliding manifold is reached. Thence, all terms related to the reference signal in the tracking error can be eliminated and high-precision tracking can be achieved while reducing chattering phenomenon. Remarkably, the detailed expressions of the derivatives of the reference signal are unnecessarily required, which simplifies the controller design and implementation. It is rigorously proved mathematically that the closed-loop system is asymptotically stable. Finally, the proposed control algorithm is applied for solving the position tracking control problem for permanent magnet synchronous motor servo systems, and experimental results verify the effectiveness and superiority.

Permanent magnet synchronous motor (PMSM) servo system is the control and execution mechanism of spacecraft, and its precise modeling is of great practical significance for improving the performance of the spacecraft. A comprehensive model considering elasticity, backlash, and friction was established based on the structural composition and transmission characteristics of spacecraft. Firstly, an elastic-dead zone model was established based on the transmission characteristics, with two mass elastic and gear backlash dead zones as the main features. Then, an improved LuGre friction model was established that considers the effects of vibration and environmental temperature, and the three models were organically combined. Finally, a method for identifying nonlinear parameters of the system using sinusoidal sweep and the least squares method was proposed, and the accuracy of the constructed model was verified. The experiment shows that the error of the simulation results is consistent with the experimental results. This method can precisely obtain the servo system model, providing theoretical support for control method research.

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.

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

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).

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.

This article proposes a novel robust method for identifying the moment of inertia of rotor shaft in surface-mounted permanent magnet synchronous motor servo systems. Superior to conventional approaches, this method enables stable identification under current control loop or poorly tuned speed loop, and can identify the moment of inertia using low-amplitude speed injection as small as 0.5 rad/s (4.8 r/min), while maintaining minimal errors. The method is based on sinusoidal signal injection and identifies the moment of inertia by analyzing the phase difference between the estimated load torque and motor speed. This approach provides a reliable one-time parameter calibration, largely insensitive to the influence of unknown disturbances, including Stribeck friction, nonlinear load, and speed quantization errors. This method can be applied to rapid autotuning of speed loop and online moment of inertia identification with low-amplitude injection, providing a foundation for high-performance control algorithms. Experimental results validate these characteristics.