Fuzzy control and gain scheduling-case study: robust stabilization of an inverted pendulum

An interactive procedure is presented for controller design of nonlinear systems by integrating available classical as well as modem tools such as fuzzy logic, and neural networks. The proposed approach is based on quasi-linear dynamic models of the plant. Classical optimal controllers for each set of operating conditions were developed. These controllers are used to construct a single fuzzy-logic gain scheduling-like controller. Adaptive-neuro-fuzzy inference system was used to construct the rules for the fuzzy gain schedule. This will guarantee the continuous change in the gains as the system parameters change in time or space. The proposed approach is applied on a well known bench mark system, the inverted pendulum.