An adaptive PID-type sliding mode learning compensation of torque ripple in PMSM position servo systems towards energy efficiency. (April 2021) - Zhang, Wenjing; Cao, Bowen; Nan, Nan; Li, Mengyue; Chen, YangQuan
Abstract: In this paper, for periodic motion tasks, combining adaptive PID-type sliding mode control (APIDSMC), model reference adaptive control (MRAC) and periodic adaptive learning control (PALC), a novel APIDSMC-PALC compensation approach towards energy efficiency is proposed to suppress the influence of torque ripple in permanent magnet synchronous motor (PMSM) servo systems. Using particle swarm optimization (PSO) algorithm, the equivalent control gain of sliding mode control is optimized to achieve energy efficiency during long-term operation. The objective of the proposed ripple compensation algorithm is to accurately approximate two dominant harmonic amplitudes in the torque ripple and generate an additional control effort for ripple compensation. Simulation and testbed experimental results demonstrate that with the proposed ripple compensation algorithm, the objective of excellent position tracking performance is ensured, and the energy efficiency is improved. Highlights: It is the first time to propose an energy-efficient coefficient optimization method. Torque ripple is estimated by using its dynamic characteristics under periodic tasks. The robustness is enhanced by adding adaptive PID-type sliding mode control.