Permanent Magnet Synchronous Motor System Research Articles

Application of sliding mode variable structure control algorithm in PMSM vector control system in complex environment.

In order to meet the increasing demand of high-performance control in industrial production, a new sliding mode variable structure control algorithm, Asymptotic Sliding Mode Control (ASMC), is designed in this study to solve the serious chattering problem of sliding mode control. Firstly, a traditional sliding mode exponential approximation law control model and a state space and control function are constructed based on sliding mode control. Secondly, by eliminating the jitter factor, ASMC algorithm is combined with sliding mode control to achieve precise control of permanent magnet synchronous motor (PMSM) and improve its performance. The experimental results indicated that in the simulation experiment, the research system tended to stabilize within 0.2-0.3 seconds, and the system chattering was significantly suppressed. And its output was smoother, the jitter amplitude was significantly reduced by 1/3, and the output torque was more stable. In addition, when the parameter H0 changed to 2H0, the overall speed curve did not change much, with only a slight overshoot. The overshoot was only 2.8%, and the change amplitude was maintained at around 25r/min, indicating that the research system had strong self stability performance. In actual experiments, the current command oscillation of the research system was significantly reduced. The local graph showed that the output fluctuation amplitude of the asymptotic approach law actual control was significantly smaller under no-load disturbance. When the H0 changed towards 2H0, the actual adjustment time was about 0.1 seconds, which was consistent with the simulation experiment. Therefore, the contribution of the research is that the ASMC algorithm can suppress the chattering problem of the system and improve the approaching speed, thus improving the speed regulation quality of the system. This new algorithm has great theoretical and practical significance for improving the performance of PMSM, and is practical in the actual vector control system of PMSM.

Energy Optimization of Marine Drive Systems with Permanent Magnet Synchronous Motors

The International Maritime Organization are introducing more and more stringent requirements concerning increasing ships’ energy efficiency. They are becoming a huge challenge for design engineers. This article proposes a method to increase the energy efficiency of mechatronic drive systems in ship systems via the use of highly efficient electric permanent magnet synchronous motors (PMSMs). An innovative control strategy is suggested. It is based on the modification of the classic PMSM control and ensuring energy optimization through a reduction in reactive power in the Active Converter–PMSM system. Analytical and simulation studies using the Matlab–Simulink program are presented. They confirm the possibility of reducing reactive power in a PMSM drive system. A verification of the results of analytical and simulation examinations was conducted at a laboratory station with the use of the Speedgoat module operating in the Rapid Control Prototyping mode. Both the simulation and experimental research results indicate the effectiveness of the proposed PMSM control method. This method has good prospects for application in energy-saving marine drive systems.

Virtual Reference-Based Fuzzy Noncascade Speed Control for PMSM Systems With Unmatched Disturbances and Current Constraints

This paper aims to develop a non-cascade speed control approach for permanent magnet synchronous motor (PMSM) systems based on the Takagi–Sugeno (T–S) fuzzy model. In non-cascade control structures, the lack of firsthand current references imposes a tricky challenge in dealing with current constraints from the circuit and unmatched disturbances caused by load torques. To this end, a virtual reference-based fuzzy non-cascade speed control scheme is proposed for PMSM systems. First, unmatched load torques are estimated by a fuzzy disturbance observer. And then, a novel virtual reference planner is constructed to inject the estimated unmatched disturbance into the control channel as feedback compensation. This improves anti-disturbance performance, while keeping the current re-sponse within the feasible domain and reducing speed overshoot. Furthermore, the non-cascade speed regulation problem is con-verted into a system stabilization problem and addressed by the composite control strategy based on the non-parallel distributed compensation. Finally, closed-loop stability with reduced con-servatism is ensured through the fuzzy Lyapunov functions and improved slack variables. Simulations and experiments show that the proposed scheme achieves excellent speed response without overcurrent even under mismatched load torque variations.

A sliding mode‐based single‐loop control strategy for permanent magnet synchronous motor drives

AbstractA simple control structure with high anti‐disturbance ability is proposed here for permanent magnet synchronous motor (PMSM) drives. The conventional cascade structure, with an outer speed loop and an inner current loop, is simplified and merged into one single‐loop controller. To enhance the dynamic performance and efficiency of the PMSM drives, an enhanced adaptive reaching law (EARL) is proposed for the single‐loop control strategy. In comparison with conventional reaching laws, the EARL can increase the convergence speed, adapt the gain to fit the system state, and reject the chattering phenomena of conventional sliding mode control. Moreover, an improved disturbance observer (DOBS) is developed to work with the main controller. The DOBS aims to enhance the estimation accuracy of real‐time unknown disturbances in the PMSM system, thereby further improving the disturbance rejection capability through feedforward compensation for the single‐loop control strategy. The EARL and DOBS thus enhance the robustness of the control strategy and ensure high dynamic performance at various motor operating conditions. The performance and efficiency of the proposed control are validated through simulations and experimental studies.

Adaptive continuous twisting control for speed regulation in PMSM

ABSTRACT Traditional vector control strategies cannot eliminate the disturbances existing in permanent magnet synchronous motor (PMSM) systems while maintaining their dynamic performances. To address this issue, this paper proposes an adaptive continuous twisting (ACT) control method to further improve the control accuracy and anti-interference ability of the PMSM system. Firstly, a continuous twisting controller is designed to generate a continuous signal, which is utilised in the speed loop. It can guarantee that the tracking error of the speed regulation system finite-time converges to zero. This not only enhances the robustness of PMSM system but also effectively weakens the control chattering. Secondly, on this basis, an ACT controller is constructed to handle the disturbances with unknown bounds in PMSM systems. Finally, simulation and experimental results show that the proposed control method can improve the performances of PMSM system.

Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor (PMSM) speed control systems with conventional linear active disturbance rejection control (CLADRC) strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances. In order to address these issues, this paper proposes an improved two-degree-of-freedom LADRC (TDOF-LADRC) strategy, which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning. PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately. Moreover, to evaluate the control performance of the TDOF-LADRC strategy, its stability is proven, and the influence of each controller parameter on the system control performance is analyzed. Based on it, a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances. Finally, experiments are performed on a 750 W PMSM experimental platform, and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

PWM harmonics reduction for dual-branch three-phase PMSMs using interleaving topology

High-frequency pulse width modulation (PWM) acoustic noise is generated by PWM switching harmonics in the dual-branch three-phase permanent magnet synchronous motor (PMSM) systems during the switching process of the drivers. Because of the special winding structure of the double branch motor, the sum of the current of the two branches reflects the high frequency vibration of the motor. This paper proposes a method using four voltage source inverters and coupled inductors with a special connection method to eliminate the carrier frequency as well as its twice, triple noise for dual-branch three-phase PMSMs. Carrier-phase-shift technique is used to change the direction of the current harmonics. Compared with the conventional method, four paralleled VSIs can be saved. The simulation results verify the effectiveness of the method.

Optimal Coordinated Control for Speed Tracking and Torque Synchronization of Rigidly Connected Dual-Motor Systems

Dual-motor systems have been broadly used to drive large inertia loads. In this article, the optimal coordinated control problem of rigidly connected permanent magnet synchronous motor (PMSM) systems is investigated to enhance the speed tracking and torque synchronization performance. First, the mathematical model of rigidly connected dual-PMSM systems is established in terms of the model of the PMSM and the characteristics of gear transmission drive. Second, to minimize the speed tracking and torque synchronization errors, a novel optimal coordinated control scheme is proposed for rigidly connected dual-PMSM systems by combining the conventional master–slave control structure and the linear–quadratic regulator control strategy. Then, taking into account the inherent two-time-scale characteristics, a composite suboptimal coordinated controller is devised through optimal problems of slow and fast subsystems. Furthermore, the closed-loop stability is proved by singular perturbation theory. Finally, simulation and experimental studies are provided to corroborate our theoretical results. It is shown that the proposed method can effectively improve the speed tracking and torque synchronization performance of the rigidly connected dual-PMSM system simultaneously.

Predefined-time smooth stability analysis of nonlinear chaotic systems with applications in the PMSM system and Hindmarsh-Rose neuron model

This article investigates the predefined-time stabilization of nonlinear chaotic systems with applications in the permanent magnet synchronous motor (PMSM) system and Hindmarsh-Rose neuron model. Distinguished from the traditional predefined-time control methods, this investigation develops the smooth control protocols, in which the discontinuous absolute value and signum functions are not used anymore, so that the unfavorable chattering phenomenon can be avoided effectively. By the Lyapunov stability analysis, the sufficient condition is derived to achieve the predefined-time stable for nonlinear chaotic systems, in which the upper-bound time estimation (TE) of arriving at the stable state is explicit in contrast to the traditional finite-/fixed-time convergence. Specifically, the analytical results are successfully applied into stabilizing the PMSM system and Hindmarsh-Rose neuron model within the predefined-time. Finally, the numerical simulations for stabilizing the chaotic PMSM system and Hindmarsh-Rose neuron model verify the effectiveness and advantages of theoretical analysis.

Optimized multi-timescale energy management strategy of a novel all-electric aircraft power system unit based on decentralized control

This paper presents an optimized multi-timescale energy management strategy (MTEMS) for a novel all-electric aircraft (AEA) power system unit, which consists of a hybrid energy storage system comprising super-capacitor (SC), battery and fuel cell (FC), as well as a dual three phase permanent magnet synchronous motor (DTP-PMSM) system serving as the propulsion system. During transient states characterized by rapid load changes, the proposed strategy effectively allocates power from the low-frequency, medium-frequency, and high-frequency domains to their respective units, namely FC unit, battery unit, and SC unit. This power allocation is achieved through decentralized droop control implemented in the proposed MTEMS, ensuring a constant and stable bus voltage throughout the operation. In addition, during the steady-state after the change of the load power, a distributed optimization method of the proposed MTEMS can calculate the ratio of power outputs between the battery and FC to maximize the operational efficiency of the fuel cell while ensuring the battery operates in an economically optimal condition. This ultimately guarantees the entire system operates under optimal operating conditions. The achievement of the output power ratio is attainable through the implementation of decentralized droop control. Finally, a 1 kW experimental platform is constructed to validate the effectiveness of the proposed MTEMS and verify the analytical results.

Chaos control in networked permanent magnet synchronous motor using Lyapunov‐based model predictive subject to data loss

AbstractThis study investigates the chaos control in the permanent magnet synchronous motor (PMSM) using a Lyapunov‐based model predictive approach subject to data loss. PMSM, as a rich nonlinear dynamic, can demonstrate chaotic behavior when its parameters are in a certain area. Thus, the performance of the system will degrade in this condition. Moreover, in some networked applications, especially in the modern automation industry, data can be lost at the sensor‐controller and controller‐actuator links. It will lead the system to illustrate the chaotic behavior. Thus, by assuming a PMSM under data loss, a Lyapunov‐based predictive model is applied to control the chaos in the PMSM in the presence of data loss. It shows that the PMSM system also be effective if the states of the system are not available or the system faces data loss. Sufficient conditions are discussed for the control of chaos in these conditions. Finally, the influence of the method on the control performance is evaluated via simulations on a nonlinear model for the PMSM.

An Improved Full-Speed Domain Sensorless Control Scheme for Permanent Magnet Synchronous Motor Based on Hybrid Position Observer and Disturbance Rejection Optimization

A sensorless control algorithm not only reduces the cost of a permanent magnet synchronous motor (PMSM) system, but also broadens its application scope. Expanding speed threshold and enhancing dynamic performance are crucial aspects. To optimize the adaptability of observers and the immunity of the controller in a full-speed domain, an improved sensorless control scheme for a PMSM based on a hybrid position observer and disturbance compensation is proposed. Firstly, the precise detection of the initial position and the scheme of starting with the load at any position are proposed based on high-frequency rotation injection, magnetic pole direction calibration and square-wave high-frequency injection (HFI). Secondly, a higher-order sliding mode observer (HSMO) is designed to improve high-speed observation performance by introducing an extended electromotive force (EEMF). Correspondingly, a speed controller called PI plus is developed utilizing a reverse control algorithm and the observed disturbance quantity, which further enhances the system’s disturbance rejection capability. Subsequently, a linearly weighted observer switching method and a linear signal withdrawal scheme are proposed to suppress torque and speed oscillations in medium-speed threshold. Furthermore, a normalized linear extended state observer (LESO) is designed to enhance rotor information estimation accuracy and enable the observation of unknown disturbances in full-speed thresholds. Finally, the effectiveness of the proposed sensorless control system is tested through experiments involving variations in speed, load, and parameter. The experimental results indicate that the proposed sensorless strategy is capable of achieving a loaded start. The designed observer switching strategy and the scheme of injection signal withdrawal contribute to a smoother acceleration process. Furthermore, load variation test results at high-speed thresholds demonstrate that the proposed controller can reduce speed drop by 45 rpm compared to a traditional PI. Additionally, the results of parameter variation testing validate the observer’s robustness in the disturbances of ψf within the range of ±0.3 pu.

Current-Constrained Adaptive Robust Control for Uncertain PMSM Drive Systems: Theory and Experimentation

In this paper, we investigate the speed tracking control problem for permanent magnet synchronous motor (PMSM) drive systems. In particular, the current constraint, parametric uncertainties, and the external load disturbance are addressed simultaneously. To deal with these issues, we first propose a system transformation scheme, which equivalently transforms a PMSM system with the current constraint into the one without any constraints, thereby reducing the difficulties in the controller design caused by the current constraint. Based on the transformed system, the adaptive parameter estimation and robust control are integrated to derive a current-constrained adaptive robust controller (CCARC), which guarantees the robust tracking performance under the current constraint, parametric uncertainties and the external load disturbance. For the closed-loop system, the Lyapunov-based analysis is provided to show the convergence and stability. Finally, the effectiveness of the proposed method is experimentally validated using a 5.5 kW PMSM.

Sliding Mode Control for Sensorless Speed Tracking of PMSM with Whale Optimization Algorithm and Extended Kalman Filter

This paper proposes a sensorless speed control strategy for a permanent magnet synchronous motor system. Sliding mode control with a whale optimization algorithm was developed for robustness and chattering reduction. To estimate the position and speed of the rotor, an extended Kalman filter using Gaussian process regression was designed. In this controller, the whale optimization method adjusts the switching gain to minimize the tracking error. However, it provides chattering reduction and robustness, owing to the adaptive gain. The extended Kalman estimator calculates the rotor speed by using the current and voltage of the motor as an observer. The observer ensures the high reliability and low cost of the controller. The noise covariance and weight matrices that validated the performance of the estimation were optimized using a regression algorithm. The Gaussian process regression was trained to approximate the best covariance and matrices from the results of the motor controller execution. The performance of the proposed method was demonstrated through simulations under several conditions of tracking speed and load torque changes.

Adaptive Terminal Sliding Mode Speed Regulation for PMSM Under Neural-Network-Based Disturbance Estimation: A Dynamic-Event-Triggered Approach

The speed regulation control issue of the networked permanent magnet synchronous motor system is investigated in this paper by utilizing a nonsingular terminal sliding mode control scheme. In order to remove the demand of the prior knowledge for possible lumped disturbance and parameter uncertainties in the permanent magnet synchronous motor system, an adaptive neural network is introduced into the proposed terminal sliding mode control scheme. Moreover, in order to ease the communication overheads of the networked system, a new dynamic event-triggered mechanism with considering the neural network estimation error is employed to schedule the signal transmission between the speed sensor and the remote sliding mode controller. The Zeno phenomena for the developed dynamic event-triggered mechanism is excluded via explicit analysis. It is further shown that by choosing suitable sliding mode parameters, the proposed control strategy can guarantee the convergence of the sliding variable into a practical sliding region as well as the ultimate boundedness of the speed regulation error. Finally, the feasibility and applicability of the proposed speed regulation strategy are demonstrated by simulation results and a real experiment.

Nonlinear speed-tracking control with overcurrent protection for uncertain permanent magnet synchronous motor systems

For the speed-tracking control of permanent magnet synchronous motor (PMSM) systems, fast dynamic response and high reference speed require a large transient current to provide sufficient electromagnetic torque. However, the excessive transient current may damage the drive circuit and threaten the system safety. Besides, it is also important to pay attention to the influence of multiple disturbances including system parameter uncertainties and unknown load torque variation. To solve these problems, we propose a nonlinear speed-tracking control approach for uncertain PMSM systems. More specifically, based on the cascade control structure and by introducing auxiliary smooth function, we first develop a nonlinear current-constrained controller (CCC) to guarantee the speed tracking, disturbance rejection, and overcurrent protection simultaneously. In order to improve the robustness of the desired performances, we further implement extended state observer (ESO) techniques to propose an ESO-based CCC (ESO-CCC). Finally, comparative experiments are implemented in a 5.5 kW PMSM platform to verify the performance of the proposed two controllers.

A New Alternating Predictive Observer Approach for Higher Bandwidth Control of Dual-Rate Dynamic Systems

Dual-rate dynamic systems consisting of a sensor with a relatively slow sampling rate and a controller/actuator with a fast updating rate widely exist in control systems. The control bandwidth of these dual-rate dynamic systems is severely restricted by the slow sampling rate of the sensors, resulting in various issues like sluggish dynamics of the closed-loop systems, poor robustness performance. A novel alternating predictive observer (APO) is proposed to significantly enhance the control bandwidth of a generic dual-rate dynamic systems. Specifically, at each fast controller/actuator updating period, we will first implement the prediction step by using the system model to predict the system output, generating a so-called virtual measurement, when there is no output measurement during the slow sampling period. Subsequently, the observation step is carried out by exploiting this virtual measurement as informative update. An APO-based output feedback controller with a fast updating rate is developed and rigorous stability of the closed-loop system is established. The superiority of the proposed method is demonstrated by applying it to control a permanent magnet synchronous motor system.

A PMSM Control System for Electric Vehicle Using Improved Exponential Reaching Law and Proportional Resonance Theory

Permanent magnet synchronous motor (PMSM) provides a very competitive technology for electric vehicle (EV) traction drive with its higher power density and higher efficiency. When the control system of PMSM for EV is affected by the change of motor parameters and the interference from the external environment, the motor system cannot provide high-quality dynamic performance in time. In the paper, an EV motor control strategy based on improved sliding mode and proportional resonance theory is proposed, in which a speed controller is designed based on the improved exponential reaching law. The improved exponential approximation law overcomes chattering in traditional sliding mode control without increasing parameters and improves the anti-interference performance of the EV. In addition, the improved proportional resonance method is used to design the current controller of the PMSM control system, and the combination of the two has been successfully applied to EV for the first time. Finally, the experiment and urban road condition test are carried out to verify. The results show that the proposed scheme can effectively improve the dynamic performance and robustness of the PMSM system for EVs.

Predefined-time Stabilization of 4D Permanent-magnet Synchronous Motor System with Deterministic and Stochastic Disturbances Using Linear Time-varying Control Input

Predefined-time Stabilization of 4D Permanent-magnet Synchronous Motor System with Deterministic and Stochastic Disturbances Using Linear Time-varying Control Input

Capacitance balance control strategy for three-phase four-switch open-winding permanent magnet synchronous motor

The open-winding permanent magnet synchronous motor (OWPMSM) system is a novel high-cost system that uses dual-inverters to control both sides of the stator to improve the performance of the motor. To save the system cost, the three-phase four-switch open-winding permanent magnet synchronous motor (TPFS-OWPMSM) system is proposed to replace the general three-phase six-switch OWPMSM system, but it brings the problem of bridge arm capacitor voltage offset. To solve the instability problem caused by capacitance, this paper carries out the state analysis and offset source analysis of the inverter capacitor voltage, and proposes a dual-inverters capacitor voltage balance control strategy. The capacitor balance control converts unstable capacitor offset voltage into current and injects the currents into the stator current loop through closed-loop correction. And this strategy includes the optimal control of different capacitors under dual-inverters with the goal of system stability. The effectiveness of the balancing strategy is verified by the simulation of various motor working conditions.