A non-intervention self-tuning method for PI control parameters in a PMSM servo system with three closed loops

The conventional three closed-loop proportional-integral (PI) control system in permanent magnet synchronous motor (PMSM) servo control necessitates the precise determination of PI parameters for each loop, as these parameters critically influence control accuracy and system stability. Currently, the selection of PI parameters for the three closed loops often relies on human intervention or subjective expertise, which can lead to inefficiencies and inconsistencies. To overcome this limitation, this study proposes a fully autonomous PI parameter self-tuning method. The method employs a layered tuning approach: the current loop parameters are optimized using an internal model control strategy, prioritizing fast servo tracking response; the speed loop parameters are derived by establishing a relationship between servo tracking speed response frequency and system stability; and the position loop parameters are determined using the residue transformation method of the Z-inverse transform, aiming to minimize the tracking error for instantaneous ramp inputs. Due to the gradual variation of motor parameters caused by environmental temperature fluctuations, the parameters involved in this method can be sequentially identified using the recursive least squares (RLS) algorithm. Specifically, only one parameter is estimated at a time, while the remaining parameters are held constant. Once the motor parameters and speed requirements are specified, this method autonomously determines the PI control parameters for the PMSM servo system, enabling automatic optimization and tuning of control parameters. This approach facilitates intelligent and adaptive PMSM servo control. The effectiveness of the proposed method is validated through experimental results, demonstrating its practical applicability in engineering contexts.