The objective of this article is to design robust speed control of a permanent magnet synchronous motor (PMSM). The mathematical model of the PMSM is highly nonlinear with uncertainties and disturbances. The most obvious method is to estimate these disturbances and design a robust controller to attenuate the effect of disturbances from the output. In this article, the load torque, which typically occurs as disturbance in the servo system, is estimated using a disturbance observer (DO). A nonlinear model of the PMSM is linearized using the Jacobian linearization around an operating point, and a state feedback controller with an integral term is designed at this operating point. Novelty of the proposed method lies in the way the DO is used to update this operating point, which is similar to the gain scheduling approach. To extend this method for a sensorless operation, a sliding-mode observer is used with the DO in cascade. The proposed scheme is validated using simulations on MATLAB/Simulink and an experimental setup using TMS320F28027. The results show improved performance as compared to traditional methods over a wide range of speed.

Disturbance-Observer-Based Sensorless Control of PMSM Using Integral State Feedback Controller

Permanent magnet synchronous motors (PMSMs) have been widely employed in the industry. Finite-control-set model predictive control (FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted. 

Finite-Control-Set Model Predictive Control of Permanent Magnet Synchronous Motor Drive Systems—An Overview

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. 

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

Permanent magnet synchronous motors (PMSMs) have been widely employed in the industry. Finite-control-set model predictive control (FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.

This paper is mainly focusing on the problem of speed tracking control for permanent magnet synchronous motor (PMSM) drive system subject to matched and mismatched disturbance. This is achieved by a novel Port-Controlled Hamiltonian control method with nonlinear disturbance observer. Different from the traditional speed-current cascade control for PMSM, the speed-current single loop controller is designed. Firstly, the Port-Controlled Hamiltonian model of PMSM is established, then the Hamiltonian speed controller is designed by using interconnection assignment and damping assignment method. However, the standard Hamiltonian controller cannot achieve the satisfying behavior in the presence of the parameter variations and external disturbance, thus a nonlinear disturbance observer is designed to estimate the lump disturbance of the system, which is used to the feed-forward compensation control. Finally, simulation and experiment on the speed control system of PMSM are implemented. The results show that the proposed method has fast speed control performance and strong robustness for the different disturbance.

/pdf/a-novel-speed-control-method-based-on-port-controlled-4eh6dav6za.pdf

A Novel Speed Control Method Based on Port-Controlled Hamiltonian and Disturbance Observer for PMSM Drives

Permanent magnet synchronous motors (PMSMs) are widely used in the field of industrial servo control, especially in high-precision applications. Owing to the periodic torque ripple caused by the cogging torque, flux harmonics, and current offsets, the speed output of the system has a periodic ripple, which affects the control accuracy of the servo system. The conventional proportional–integral controllers cannot reject torque ripple and are highly dependent on motor parameters. This limits the control performance when a PMSM is used as a high-precision servo system. Thus, this paper proposes a combination of model predictive control (MPC) and iterative learning control (ILC) to not only speed up the response time of the system but also effectively reduce the speed ripples. MPC updates the predictive model in real time through feedback and evaluates the system output and control rate according to the cost function. It obtains an optimal control sequence for the next moment and has good parameter robustness and fast response. ILC records the speed of ripple signals over an entire cycle and then uses those signals to compensate for the control signal in the next cycle. It is capable of reducing the periodic speed ripples. The experimental verification of the schemes was conducted on a digital signal processor–field programmable gate-array-based platform. The experimental results obtained confirm the effectiveness of the proposed MPC–ILC scheme.

/pdf/speed-ripple-minimization-of-permanent-magnet-synchronous-325so0dmjc.pdf

Speed Ripple Minimization of Permanent Magnet Synchronous Motor Based on Model Predictive and Iterative Learning Controls

This paper reports the optimal speed control of a permanent magnet synchronous motor (PMSM) system. The predictive control method is an effective strategy for a fast dynamic response. The undesirable performance in the presence of system disturbances, including internal model uncertainties and external load disturbances, is analyzed. To achieve a fast response and ensure stronger robustness and improved disturbance rejection performance simultaneously, a robust generalized predictive controller (GPC) with a high-order terminal sliding-mode observer (HOTSMO) is proposed for a PMSM control system. The proposed observer can estimate the unknown disturbances with chattering elimination. A feed-forward compensation based on the estimated disturbances is provided to the predictive speed controller. The simulation and experimental results show that the proposed control method can achieve a better speed dynamic response and a stronger robustness.

/pdf/robust-speed-control-for-permanent-magnet-synchronous-motors-5byz34bz4s.pdf

Robust Speed Control for Permanent Magnet Synchronous Motors Using a Generalized Predictive Controller With a High-Order Terminal Sliding-Mode Observer

This paper reports on the optimal speed control problem in permanent magnet synchronous motor (PMSM) systems. To improve the speed control performance of a PMSM system, a model predictive control (MPC) method is incorporated into the control design of the speed loop. The control performance of the conventional MPC for PMSM systems is destroyed because of system disturbances such as parameter mismatches and external disturbances. To implement the MPC method in practical applications and to improve its robustness, a compensated scheme with an extended sliding mode observer (ESMO) is proposed in this paper. Firstly, for observing if and when the system model is mismatched, the ESMO is regarded as an extended sliding mode parameter observer (ESMPO) to identify the main mechanical parameters. The accurately obtained mechanical parameters are then updated into the MPC model. In addition, to overcome the influence of external load disturbances on the system, the observer is regarded as an extended sliding mode disturbance observer (ESMDO) to observe the unknown disturbances and provide a feed-forward compensation item based on the estimated disturbances to the model predictive speed controller. The simulation and experimental results show that the proposed ESMO can accurately observe the mechanical parameters of the system. Moreover, the optimized MPC improves the dynamic response behavior and exhibits a satisfactory disturbance rejection performance.

https://www.mdpi.com/1996-1073/12/10/1857/pdf

Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

This paper concentrates on a robust resonant control strategy of a permanent magnet synchronous motor (PMSM) for electric drivers with model uncertainties and external disturbances to improve the control performance of the current loop. Firstly, to reduce the torque ripple of PMSM, the resonant controller with fractional order (FO) calculus is introduced. Then, a robust two degrees-of-freedom (Robust-TDOF) control strategy was designed based on the modified resonant controller. Finally, by combining the two control methods, this study proposes an enhanced Robust-TDOF regulation method, named as the robust two degrees-of-freedom resonant controller (Robust-TDOFR), to guarantee the robustness of model uncertainty and to further improve the performance with minimized periodic torque ripples. Meanwhile, a tuning method was constructed followed by stability and robust stability analysis. Furthermore, the proposed Robust-TDOFR control method was applied in the current loop of a PMSM to suppress the periodic current harmonics caused by non-ideal factors of inverter and current measurement errors. Finally, simulations and experiments were performed to validate our control strategy. The simulation and experimental results showed that the THDs (total harmonic distortion) of phase current decreased to a level of 0.69% and 5.79% in the two testing environments.

Torque Ripple Suppression of PMSM Based on Robust Two Degrees-of-Freedom Resonant Controller

Gaussian process-based parameter identification and model current predictive control strategy of PMSM

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