On The New Control Stratergys For High Precision AC Servo Drive Systems

The simplified mathematical model of an AC Servo-Drive-System is theoretically of 2-nd and linear, but there exist really nonlinearities and coupling of multi-variables. The response speed of the system is further very fast. For these characteristics, this paper deal with two kinds of control strategies that are model-necessary and model-free respectively.By using coprime decomposition of polynomial matrices and structure variation of controllers, the simplified synthesis method of linear regulators achieved the arbitrary assignment of closed-zeros and poles of square and non-square transfer matrices without necessity of solving complicated Diophantine matrix equations.The hybrid H₂ and H^∞ robust control strategy is able to make thesystem satisfy steady and transient requests simultaneously. The non-recursive optimal design procedure of close loop eigen values with participation of eigenvectors has a global optimality. With the problem of non-disturbance transportation of weightings being solved, the variable structure neuron controller, that is realized in fact by only one network, has all the advantages of single neuron PID- and BP network-controllers. A hybrid algorithm combining PID-BP and revised Solis&Wets random optimal method has a very fast convergence speed and can achieve the global minimum in a limit number of recursions. The neuron network realized fuzzy controller with function of weightings-learning is proved to be superior to normal fuzzy controllers in control precisions.All the concerned control strategies are supported with the simulation results that are made on the experimental frequency domain model of the AC200 servo drive system.