Performance Optimization For Permanent Magnetic Synchronous Motor Based On Advanced Control Strategies

In practical application, the request to control precision of permanent-magnet synchronous-motor (PMSM) is getting higher and higher. Especially in some domains with higher motor performance requirements such as robot, aerospace, precise electronic instrumentation and so on, the rapidity, stability and robustness of system have been important targets that determining PMSM performance. Traditional motor systems usually depend on PID control, which is a kind of linear control in essence. If a plant has nonlinear behaviors or varying parameters, the PID controller with constant parameters is unable to maintain the initial performance index. In the process of tunning PID parameters, the defined parameter values are not global but partial optimums. The actual motor system has many characteristics such as non-linearity, parameter time-variability and complex in modelling et al, therefore a normal PID controller is difficult to resolve the contradiction between dynamic quality and static precision fundamentally.The study and application of advanced control strategies (intelligent control, optimization algorithm, etc.) have opened a new door for controlling complex PMSM systems. Advanced control strategies not only can get rid to the dependence on models of plants, but also have processing ability and robustness in processing inaccuracy and uncertainty questions, thus it's an inevitable tendency to introduce advanced control strategies into PMSM control. According to different goal-realizing systems, responding advanced control strategies are chosen and combined to PID controllers, which will make the PMSM performances in various aspects have pointed optimization, and enable its control precision to obtain remarkable enhancement finally. To guarantee the research goal in performance optimization for PMSM, which has typical dynamic, time-variable and nonlinear characters, this paper is to study a problem about the work characteristics and control mechanisms of sine-wave and square-wave PMSM firstly. By the building of mathematical models, the overall analysis will be carried on to corresponding control system. Aiming at the nonlinearity and highly coupling of PMSM, closed-loop systems with feedback loops are going to be design on the way of vector-control. Combined with normal PID control, several kinds of advanced control strategies, such as fuzzy control, neural network, genetic algorithm, artificial immune algorithm and so on, are applied to controller design for PMSM speed systems, servo systems and synchronous-drive systems so as to satisfy the requests of different control systems on motor dynamic and static performance and follow the stress on speed-regulating or track behavior. Experimental results demonstrate that, compared with traditional PID control, the advanced control strategies bring better dynamic performance, anti-disturbance ability and stronger robustness to PMSM and enhance control precision in its system distinctly. The findings confirmed that advanced control strategies are effective and feasible on performance optimization for PMSM.