Enhancing Servo System Performance : Robust Nonlinear Deadbeat Predictive Current Control for Permanent Magnet Synchronous Motors

Abstract: The Permanent Magnet Synchronous Motor (PMSM, also known as the servo motor) is a crucial component within robotic servo systems. To optimally respond to the torque demands sent from the high-level motion controller, the PMSM current controller must track the reference with speed and precision. Nevertheless, the operation of servo motors could be compromised due to the nonlinearity of flux linkage and inaccuracies in parameters induced by unpredictable fluctuations in temperature. This Master’s thesis proposes a novel Robust Nonlinear Deadbeat Predictive Current Control (RN-DPCC) scheme to counter these challenges effectively. The nonlinear mappings between flux linkage and current on the dq-axis are established using polynomial fitting based on experimental data. Furthermore, the Nonlinear Deadbeat Predictive Current Control (N-DPCC) is derived using nonlinear feedforward. Meanwhile, Delayed Integral Action (DIA) is introduced as a robustness-enhancing measure for N-DPCC, thus evolving it into the Robust N-DPCC (RN-DPCC). Compared to conventional Integral Action (IA), DIA effectively curtails overshoot triggered by integral error and accelerates the current transient without incorporating additional tunable parameters. Numerical simulations that leverage the mathematical modeling of the converter and nonlinear PMSM are implemented using fundamental blocks in Simulink, which replicates the actual experimental setup employed within the Motor Control Lab at ABB Corporate Research. The effectiveness of employing nonlinear feedforward compensation is confirmed through a comparative analysis of the simulation results from N-DPCC and conventional Deadbeat Predictive Current Control (DPCC). The enhancements in transient response brought about by DIA are demonstrated through a comparison of RNDPCC and N-DPCC with IA. The robustness of RN-DPCC is demonstrated by comparing it with N-DPCC under conditions where parameter inaccuracies are present.