Title :
H∞ adaptive fuzzy control for high performance brushless drives
Author :
Chouika, Ahmed Rubaai Mohamed F ; Bofah, Peter ; Noga, Donald F.
Author_Institution :
Dept. of Electr. Eng., Howard Univ., Washington, DC, USA
Abstract :
A new design method for a high performance brushless drive system employing both H∞ optimal control design and fuzzy control design is described in this paper. The fuzzy control design is equipped with an adaptive learning algorithm to achieve H∞ tracking performance with external disturbances. It gives elevation to the selection of optimal performance weights without any trial and error attempt. The objective is to establish a link between H∞ optimal, control design and fuzzy control design, so as to provide H∞ tracking design with more intelligence and achieve better performance with fuzzy control design. In this study, the effect of both fuzzy logic approximation error and external disturbance on the tracking error is attenuated to an assigned level. The control strategy does not require explicit knowledge of the motor/load dynamics which is a useful feature when dealing with parameter and load uncertainties. The robustness of the proposed methodology is displayed for different types of trajectories. Simulation results suggest that the effect of both the fuzzy approximation error and external disturbance on the tracking error can be attenuated efficiently by the H∞ adaptive fuzzy control. Accordingly, the proposed design method is suitable for the robust tracking control of the uncertain nonlinear drive systems and is an attractive control design philosophy. To the best of the author´s knowledge, however, this control design represents the first such attempt for high performance drive systems
Keywords :
DC motor drives; H∞ control; approximation theory; brushless DC motors; control system analysis; control system synthesis; fuzzy control; machine control; machine theory; nonlinear control systems; robust control; uncertain systems; H∞ adaptive fuzzy control; H∞ optimal control design; H∞ tracking performance; adaptive learning algorithm; control simulation; external disturbances; fuzzy control design; fuzzy logic approximation error; high-performance brushless DC motor drives; intelligence; load uncertainties; optimal performance weights selection; parameter uncertainties; performance; robustness; tracking error; Adaptive control; Algorithm design and analysis; Approximation error; Control design; Design methodology; Fuzzy control; Fuzzy logic; Optimal control; Programmable control; Uncertainty;
Conference_Titel :
Industry Applications Conference, 2000. Conference Record of the 2000 IEEE
Conference_Location :
Rome
Print_ISBN :
0-7803-6401-5
DOI :
10.1109/IAS.2000.881953