A Two-step Tuning Method of Control Parameters for Permanent Magnet Synchronous Linear Motor

Taking the tubular permanent magnet synchronous linear motor(TPMSLM) system as the research target, a kind of parameters tuning strategy for balancing dynamic tracking performance and system stability is proposed. First, based on the mathematical model of the servo system, the parameters of the control system are initially tuned according to the index of the frequency-domain optimal model from the inner loop to the outer loop. Second, the neural network is used to establish the correlation model between the control parameters and the error evaluation index. Subsequently, the optimal parameters were obtained by Pareto optimal front. The two-step tuning method makes up for the defects of model-based tuning or rule-based tuning, giving the optimal solution set without weakening the weight of different objectives. The experimental results show that the optimized control system has strong anti-interference ability and good dynamic performance.