Identification and Compensation Control of PMSM LuGre Friction Model Parameters Based on Improved Dung Beetle Optimizer

To address the impact of nonlinear friction on the dynamic and static performance of permanent magnet synchronous motors (PMSM) in servo systems, an improved Dung Beetle Optimizer (IDBO) method is proposed for identifying Lu-Gre friction model parameters and implementing feedforward compensation. By introducing segmented PWLCM chaotic mapping, along with an improved dynamic sine and adaptive weight factor update for the Dung Beetle iterative model position, the convergence speed is accelerated while balancing the capabilities of global and local search. To identify the LuGre friction model parameters, the improved DBO reduces the identification error from 10% to within 2%, thereby enhancing accuracy. Finally, a feedforward compensation controller is designed and integrated into the speed loop of the servo system motor. Simulation experiments demonstrate that feedforward compensation based on the LuGre model effectively improves the accuracy of the servo system and reduces the impact of nonlinear friction on both dynamic and static performance.