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

Abstract

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. INDEX TERMS Iterative learning control, model predictive control, PMSM control, speed ripple.

Design of an Observer-Based Architecture and Non-Linear Control Algorithm for Cogging Torque Reduction in Synchronous Motors

“…In [22] the authors propose a combination of model predictive control (MPC) and 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.…”

“…As in [17][18][19][20][21][22], the majority of the works in literature approaches the cogging torque problem in the context of a speed control system, actually the presence of the cogging behaviour creates more problems in position control loop than in the speed one. This is due to the fact that the wavelike trend is more a problem in applications in which is required a high precision in rotor axis positioning.…”

Artificial Intelligence-Aided Model Predictive Control for a Grid-Tied Wind-Hydrogen-Fuel Cell System

“…The scheme is capable of faulttolerant operation. An MPC scheme in [40] has reduced the torque ripples in a permanent magnet machine. The study emphases the importance to establish an objective model while exploring an MPC scheme.…”

Speed Regulation Based on Adaptive Control and RBFNN for PMSM Considering Parametric Uncertainty and Load Fluctuation

“…Permanent magnet synchronous motor (PMSM) has been extensively used in industrial applications, such as wind power systems, medical instruments, consumer electronics, robots, and electric vehicles due to its inherent characteristics of small size, simple structure, high reliability, and good torque and speed control characteristics [1]- [3]. In these applications, good speed control performance is important.…”