Adaptive model-based control of non-linear plants using neural networks and fuzzy logic

We describe in this paper adaptive model-based control of the inverted pendulum using a new hybrid approach combining neural networks and fuzzy logic. Intelligent control of complex plants is a difficult problem because the dynamics of these systems is highly non-linear. We describe an intelligent system for controlling the inverted pendulum to illustrate our new hybrid approach for adaptive control. We use the mathematical model of the inverted pendulum as s reference model in the control, and a set of fuzzy rules for representing the expert knowledge in controlling the non-linear dynamical system. We also consider a neuro-fuzzy approach to optimize the parameters of the fuzzy system for control.