Fuzzy optimization techniques applied to the design of a digital PMSM servo drive

This paper presents a novel design approach by applying gradient optimization with fuzzy step-sizing techniques to the design of a digital permanent magnet synchronous motor (PMSM) servo drive. The servo specifications and design variables are specified and analyzed to formulate a controller optimization problem. The servo responses are then fed back to evaluate the overall system performances, which can be expressed as objective functions with respect to the servo control parameters. According to the objective functions and design specifications, the servo control parameters can be properly tuned toward their optimal values by using the proposed optimization techniques. In order to improve the convergent rate of the optimization process, a fuzzy-logic based step-size tuning strategy is presented. Because of the nonlinear property of the digital servo drives, the tuned servo control parameters may be only optimal for a particular operating point, therefore, once the optimum design is achieved, the proposed fuzzy optimizing controller can perform as an intelligent tuner for on-line gain adaptation under different loading conditions. The proposed fuzzy optimization servo tuner has been realized under a PC-MATLAB-based environment with an on-line controlled digital PMSM servo drive. Simulation and experimental results indicate that the control parameters of a digital PMSM servo drive can be optimized for its dynamic responses under various load conditions.