Torque Ripple Minimization and Control of a Permanent Magnet Synchronous Motor Using Multiobjective Extremum Seeking

In this paper, a multiobjective extremum-seeking (MOES) approach is proposed for torque control of a permanent magnet synchronous motor and minimization of its torque ripple. The latter aspect is important in human–machine interface applications such as haptic interfaces requiring smooth torque profiles at slow speeds. The proposed MOES scheme combines an adaptive iterative learning control method with an adaptive proportional-integral (PI) controller, which makes the system less sensitive to load disturbances and improves the control performance for torque regulation during transient events. Experiments are performed on a proof-of-concept exercise machine that generates desired torque profiles and mechanical impedance based on user's preference. The performance of the proposed controller is further compared with a recently proposed adaptive PI controller. The experimental results validate the effectiveness of the proposed controller in terms of torque ripple suppression, steady-state and transient performance, and load disturbance rejection.