Supervisory fuzzy control of non-linear motion system

High performance AC drives requiring good position command tracking and load regulation responses are increasingly demanded in industrial applications. The adaptive control methods that take plant disturbances suppression into account are being used for driving either nonlinear systems or nonconstant parameters systems. Generally, the adaptation is achieved by using the model reference approach or recursive plant parameter identification. Instead of this paper proposes a single self-tuning control based on supervisory fuzzy adaptation. The supervisor changes the integral term of a standard PDF controller for adapting it to the plant evolution according to the dynamics of the system. The fuzzy logic adaptive strategy has been readily implemented, with very good tracking and regulation characteristics. Stability of the developed controller has been also established in the Lyapunov sense, and computing simulations and experimental results demonstrate the robustness of the suggested algorithm in contending with varying load and torque disturbance.