Permanent Magnet Synchronous Motor Servo Research Articles

A New Fuzzy Sliding Mode Control Method for Permanent Magnet Synchronous Motor Servo System Based on Optimization of Fuzzy Rules

Aiming at the problems of inherent chattering of traditional sliding mode control system of permanent magnet synchronous motor and further improving the control precision, a new fuzzy exponential reaching law sliding mode control method optimized by improved differential evolution (DE) algorithm (DEFSMC) is proposed in this article. A new hyperbolic tangent function with fuzzy boundary layer is proposed to instead of the traditional switching function, and the improved DE algorithm is used to optimize the fuzzy rules of parameters in sliding mode controller. Simulation and experimental results prove that the proposed strategy can effectively reduce the chattering and overshoot, and improve the response speed and robustness of the system. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Global position tracking control of PMSM servo system via internal model approach and experimental validations

SummaryIn practical engineering, load torque disturbance and parameter uncertainties are two important factors, which may deteriorate the tracking accuracy of permanent magnet synchronous motor (PMSM) servo system. Therefore, its global position tracking control problem is a challenging task when the load torque disturbance is time‐varying and the motor parameters are unknown. In this article, an internal model controller based on global robust output regulation (GROR) theory is proposed to achieve this control objective. In particular, we first formulate the global position tracking control problem as a GROR problem. Then, the GROR problem is converted into a global robust stabilization problem of an augmented system by constructing an appropriate internal model. Finally, we can stabilize the augmented system by a global stabilization controller instead of local stabilization controller used in the recent work, which guarantees global position tracking and disturbance rejection of PMSM servo system. The excellent position tracking performance of our design is demonstrated by both simulation and experimental results.

An Improved Extended State Observer-Based Composite Nonlinear Control for Permanent Magnet Synchronous Motor Speed Regulation Systems

This paper addresses the problems of an improved extended state observer (ESO)-based composite nonlinear control for the permanent magnet synchronous motor (PMSM) speed regulation systems, which is primarily constituted by a linear ESO-based feedforward compensation and nonlinear proportional feedback (NPF) control law. Firstly, by taking the parametric perturbations and external disturbances into account, a novel linear ESO is designed and analyzed to estimate the lumped disturbance, such that the system anti-disturbance performance is preserved. Meanwhile, the estimation of system state is also performed. Then, an optimal control synthesis function-based tracking differentiator (TD) is developed to arrange the transition dynamic for the reference velocity value, while its high quality differential signal is facilitated. Furthermore, an adaptive proportional control law is proposed, resulting in the eventual composite nonlinear strategy by incorporating the estimate values into the designed NPF controller. Finally, a PMSM servo system is studied to demonstrate the advantages and effectiveness of the proposed approaches.

Continuous Nonsingular Fast Terminal Sliding Mode Control for Speed Tracking of PMSM Based on Finite Time Disturbance Observer

A continuous nonsingular fast terminal sliding mode (CNFTSM) control strategy with an automated double power reaching law is proposed to improve the performance of speed dynamic response and accuracy tracking for the permanent magnet synchronous motor (PMSM) servo system. In pursuit of robustness against system uncertainties, a finite-time convergent extended state observer (ESO) is designed to estimate external disturbances, parameter variation, and unmodeled dynamics as a feedforward compensation to the output feedback control system. The developed controller, based on Lyapunov stability theory analysis, can guarantee finite time stability from any initial state in the presence of internal and external disturbances. The modified sliding mode reaching law can achieve enough convergence rate compared with the exponential reaching law, and the inherent chattering of sliding mode is reduced when system states approach the equilibrium point. Theoretical analysis and simulation results demonstrate that the proposed composite controller can achieve higher performance than the conventional sliding mode method.

Adaptive Control of PMSM Servo System for Steering-by-Wire System With Disturbances Observation

Intelligent driving system requires more precise and reliable steering control, and steering-by-wire (SBW) technology can better adapt to the development of autonomous driving. The permanent magnet synchronous motor (PMSM) servo system is the actuator of the SBW. Aiming at the uncertainties of the PMSM servo system, a new adaptive control method for the PMSM servo system is proposed. Parameter adaptive laws are designed for each slowly varying parameter and unknown parameter, and robust terms are introduced to the adaptive laws for the parameter uncertainties. The convergence speed of the parameter adaptive law proposed can be improved by adjusting the parameters related to the convergence rate. To reduce the scope of disturbance uncertainties, the steering load disturbances are divided into a bounded unknown time-varying part and a predictable time-varying disturbance. Based on the Luenberger observer, the prediction term of the load torque is estimated by the current of PMSM in real time. By introducing boundary estimation and robust term of unknown disturbance into the control law and parameter adaptive law, respectively, the uncertainties of parameters and unknown external disturbance can be compensated. Simulation and hardware-in-the-loop tests are carried out on the SBW platform. Experiments show that the control strategy of the PMSM servo system designed in this article has good tracking accuracy and stability.

Speed control of PMSM based on neural network model predictive control

In order to optimize the control performance of permanent magnet synchronous motor (PMSM) servo system, an improved model predictive control (MPC) scheme based on neural network is investigated in this paper. First, the dynamic characteristics of the PMSM are approximated by echo state network (ESN) to predict the future speed. Particle swarm optimization (PSO) is used to train ESN output weights to solve the problem that instability of output weights caused by pseudo-inverse matrix in ESN weight solving algorithm, called PSO-ESN, which enhances the stability and the accuracy of ESN speed prediction. That provides future plant output for control optimization of the predictive control. Furthermore, in order to reduce the computational cost and improve the response performance of the controller, a fast gradient method (GM) is applied to minimize the quadratic performance index and solve the optimal control input sequences. The simulation results under three different working conditions show that the PSO-ESNMPC controller designed in this paper reduces the overshoot by 5.87% and the rise time by 0.036 s compared with the reference controllers and has better robustness under parameter changes and load disturbances.

Design of Permanent Magnet Synchronous Motor Servo System Based on Improved Particle Swarm Optimization

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.

A Mixed SVPWM Technique for Three-Phase Current Reconstruction With Single DC Negative Rail Current Sensor

The single current sensor operation (SCSO) has attracted widespread attention in the motor drive system because of its ability to reduce cost and volume. However, when the SCSO is used with the conventional space vector puleswidth modulation (SVPWM) technique, the current reconstruction unobservable area in the sector boundary and low modulation area will degrade the accuracy of sampling data. In this article, a mixed SVPWM (MSVPWM) control scheme is proposed to eliminate the unobservable area. With the proposed scheme, the zero vectors (<inline-formula><tex-math notation="LaTeX">${{{\bm V}}_{{\rm {0}}}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">${{{\bm V}}_{{\rm {7}}}}$</tex-math></inline-formula>) are replaced by the complementary effective vectors to achieve the same effect in the sector boundary and low modulation area, and the SVPWM is applied to the remaining space vector plane. These inserted effective vectors make the current observation window time prolonged to ensure that the dc-link current data can be accurately acquired in the entire space vector plane. Hence, the high-quality reconstruction of the phase current can be realized with less impact on the output of current ripples and reconstruction errors. Moreover, the relationship between the rotation speed and the increase in switching losses under different switching frequencies is quantitatively analyzed. The effectiveness of the MSVPWM reconstruction algorithm was verified by experimental results obtained from a permanent-magnet synchronous servo motor.

Model predictive position control of permanent magnet synchronous motor servo system with sliding mode observer

AbstractIn order to improve the control accuracy and robustness of permanent magnet synchronous motor (PMSM) servo system, a new non‐cascade predictive control strategy is proposed to replace the traditional three‐closed‐loop servo control in this paper. The design process is as follows. First, the state variables and a discrete‐time state space model of motor are defined; meanwhile, the lumped term of disturbance is included in the motor model. Second, the optimal cost function is chosen to design the model predictive controller (MPC). Then, according to the uncertain parameters and external disturbance, the sliding mode observer (SMO) is introduced to estimate and compensate the disturbance. Finally, the comparative experimental result proves that the proposed predictive control method not only has less regulation parameters but also has high position tracking accuracy and strong anti‐interference ability even under different conditions.

Voltage Control of IPMSM Servo Drive in Constant Power Region With Intelligent Parameter Estimation

A novel voltage control scheme for an interior permanent magnet synchronous motor (IPMSM) servo drive in the constant power region with intelligent estimation of the motor parameter is proposed in this study. In the novel voltage control scheme, a feedforward voltage angle controller is proposed where an intelligent parameter estimation method by using a wavelet fuzzy neural network (WFNN) is developed to estimate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis inductance online. In this study, in order to minimize the copper loss, a flux-weakening (FW) control scheme under maximum phase voltage is developed first. Then, an adaptive backstepping based nonlinear controller (ABNC) considering nonzero <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current is developed to improve the robustness of the speed control. The Lyapunov stability theorem is used to derive the adaptive law of the online estimation of the lumped uncertainty to ensure the asymptotical stability of the ABNC. Moreover, a feedforward voltage angle controller is developed for the voltage control where the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current controller is retained in order to ensure the steady-state performance of the control system. Furthermore, the WFNN is adopted to estimate the actual <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis inductance value online for the feedforward voltage angle controller to improve the dynamic response. In addition, some experimental results are demonstrated to verify the effectiveness of the proposed voltage control scheme with ABNC in the constant power region.

Transfer Mechanism Analysis of Injected Voltage Harmonic and its Effect on Current Harmonic Regulation in FOC PMSM

Harmonic injection method is widely used in the suppression of current harmonic and torque ripple in field-oriented control (FOC) permanent magnet synchronous motor (PMSM) servo system. However, under some working conditions of FOC PMSM, the harmonic injection method fails to suppress the current harmonics and causes oscillation. To analyze the cause of oscillation, the transfer mechanism of injected voltage harmonic is analyzed in this article, and the relation between injected voltage harmonic and current harmonic is derived. The theoretical analysis results show that the relation between harmonics will change with motor speed and parameters of FOC PMSM. When the relation between harmonics is reversed, the existing harmonic injection method will fail and cause harmonic oscillation. To solve this problem, a simple improvement of the harmonic injection method is proposed in this article based on the proposed close-loop model. The correctness of the mathematical derivation and the effectiveness of the proposed method is evaluated by experiment and simulation.

A large-stroke rapid motion controller for servo applications with speed and control constraints

Large-stroke rapid motion is required in many industrial servo systems (e.g. pick-and-place applications), on which constraints of control input and motion speed are usually imposed. This paper presents a hybrid control scheme for large-stroke rapid motion in such systems. The controller resorts to the time-optimal control (TOC) for maximum acceleration initially and then switches into a linear control law to achieve smooth settling. A speed regulation stage is inserted in the tracking process to prevent violating the speed constraint. To tackle the unmeasured speed and unknown disturbance, an extended state observer (ESO) can be included in the controller. The controller is applied to a permanent magnet synchronous motor (PMSM) servo system for large-stroke position regulation. Digital simulation via MATLAB is conducted first, followed by an experimental verification using a TMS320F28335 board. The results confirm that the proposed controller can track a wide range of target references with desirable performance under speed constraint and load disturbance and has a competitive advantage over the popular active disturbance-rejection control (ADRC) scheme.

Intelligent Permanent Magnet Motor-Based Servo Drive System Used for Automated Tuning of Piano

This paper presents an intelligent permanent magnet synchronous motor-based servo drive system used in automated piano tuning applications. The permanent magnet synchronous motor-based drives are able to improve the accuracy of the piano tuning process in comparison with the traditional direct-current motor-based and step motor-based servo drives. To explain the techniques, firstly, the structure and principles of the automated piano tuning devices with a surface-mounted permanent magnet synchronous motor-based drive system integrated are introduced, illustrating that it is feasible to implement the proposed piano tuning strategy. Secondly, the piano tuning devices have two functions: low-speed rotation and position holding. To ensure that the surface-mounted permanent magnet synchronous motor can rotate stably over the low-speed range with strong anti-interference capacity, a double closed-loop speed-regulation-based control scheme is employed. And to ensure high position control performance, a fuzzy-adaptive triple closed-loop position-regulation-based control scheme is employed. It terms of the control schemes, it deserves to be mentioned that main contributions include, firstly, the parameters of the proportional integral controllers in the double closed-loop speed-regulation structure is tuned relying on both stability and bandwidth analyses. Then, a fuzzy-adaptive proportional integral controller is specially-designed for the triple closed-loop position-regulation to adapt to the piano tuning applications. Simulation is conducted on a 20 rpm three-phase permanent magnet synchronous motor servo drive-based piano tuning system to validate the proposed piano tuning method and to verify the proposed control techniques.

The Dual-Core Sliding Mode Control Technology of Permanent Magnet Synchronous

Based on the structure and working principle of permanent magnet synchronous motor, a mathematical model suitable for engineering practice is established. For the system chattering problem caused by sliding mode control, a variable gain sliding mode controller is proposed to suppress chattering. Based on the MTLAB simulation platform, the permanent magnet synchronous motor servo control system model is designed and verified by simulation to verify the static and dynamic performance of the system. An experimental platform with DSP and FPGA as the core is built, and a new sliding mode control algorithm with DSP and FPGA as the core is verified. To verify the feasibility of the control strategy described in this article, the load experiment was carried out on the platform. Simulation and experimental results shown that the permanent magnet synchronous motor servo system based on dual-core sliding mode control technology has high response speed, high steady-state accuracy and robustness, and has good static and dynamic performance.

Finite-time adaptive fuzzy asymptotic tracking control for PMSMs with full-state constraints

In this paper, a finite-time adaptive fuzzy control approach is developed for asymptotic tracking control of permanent magnet synchronous motors (PMSMs) with full-state constraints. Multiple nonlinear state-dependent functions are introduced in the control design, such that the rotor position, the rotor angular velocity and the currents of the d-q axis are confined to effective ranges. By combining backstepping control design with the finite-time control technique, a novel adaptive fuzzy tracking control is developed, which can accelerate the convergence speed and improve the robustness of the PMSM servo systems. Moreover, the asymptotic tracking control can be achieved with the aid of a scaling function. It is proven that all signals of the closed-loop system are uniformly ultimately bounded, and the position tracking error can converge to zero asymptotically in finite time. Finally, the simulation results are provided to verify the effectiveness of the proposed control approach, and some comparisons are given to show the rapid and accurate position tracking performance.

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

In this paper, based on LuGre friction model, a compensation method by combining of model reference adaptive control and periodic adaptive learning control (MRAC-PALC) is proposed to eliminate the adverse influence of nonlinear friction disturbance on tracking performance in permanent magnet synchronous motor (PMSM) servo systems under periodic task conditions. Specifically, the controller consists of a linear algorithm with PD, feedforward and velocity feedback components and a nonlinear friction compensator which is divided into two parts as follows: in the first time period, an MRAC algorithm is developed to ensure the boundedness of tracking errors; from the second time period, a PALC compensation algorithm, which learns from past information and updates the controller parameters in real time, is deployed to accurately capture the friction dynamics and guarantee the tracking performance. The stability of the proposed MRAC-PALC approach is guaranteed through Lyapunov stability theorem. Some comparative simulations and experiments are conducted to illustrate the superiority of the proposed MRAC-PALC strategy.

Control Circuit design of permanent magnet synchronous motor control system based on DSP

This paper introduces the design and implementation of hardware circuit of permanent magnet synchronous motor Servo Controller Based on DSP.In this scheme,TMS320F28335 is used as the control core, and drv8312 is used as the three-phase motor driver chip. The main control circuit, communication circuit, drive circuit, current feedback circuit and protection circuit are designed in detail. The reliability of the control circuit is verified by experiments, and the servo control of PMSM is realized.

Design and analysis of permanent magnet synchronous servo motor with low rotational inertia and high torque density

Aerospace servo motor has the characteristics of strong load capacity, fast response and high control accuracy. To satisfy the design target of high dynamic performance and low weight, the high magnetic loading ironless-core array rotor structure is applied to balance the low rotational inertia and high torque density of permanent magnet servo system.

Improved BP-NN Controller of PMSM for Speed Regulation

We have studied the speed regulation of the permanent magnet synchronous motor (PMSM) servo system in this paper. To optimize the PMSM servo system's speed-control performance with disturbances, a non-linear speed-control technique using a back-propagation neural network (BP-NN) algorithm for the controller design of the PMSM speed loop is introduced. To solve the slow convergence speed and easy to fall into the local minimum problem of BP-NN, we develope an improved BP-NN control algorithm by limiting the range of neural network outputs of the proportional coefficient Kp, integral coefficient Ki of the controller, and add adaptive gain factor β, that is the internal gain correction ratio. Compared with the conventional PI control method, our improved BP-NN control algorithm makes the settling time faster without static error, overshoot or oscillation. Simulation comparisons have been made for our improved BP-NN control method and the conventional PI control method to verify the proposed method's effectiveness.

Research of Active Disturbance Rejection Controller Design for PMSM Servo System

In the permanent magnet synchronous motor (PMSM) speed control system, an improved active disturbance rejection control strategy with higher tracking accuracy for time-varying input is proposed. The traditional active disturbance rejection controller is mainly used for fast and static-free tracking of step signals, but there is a large tracking error for time-varying signals, which limits the application of active disturbance rejection controller. In this paper, the theoretical analysis of the existence of steady-state error is carried out, and then an improved speed active disturbance rejection controller (ADRC) with derivative feedforward and parallel linear extended state observer(P-LESO) is designed to reduce the tracking error of the system. In order to observe and compensate the reverse electromotive force in real time and reduce the current following error, a current loop linear active disturbance rejection controller is designed. By constructing Simulink simulation model for verification, the control system not only improves the tracking accuracy of PMSM for time-varying input, but also has a good dynamic performance for step input.