Automatic design of nonlinear controllers with optimal global performance using best estimate directed search and continued propagation cell mapping

The paper describes an optimal nonlinear control design method which consists of using an analysis tool, continued propagation cell mapping (CPCM), as feedback to the synthesis tool, best estimate directed search (BEDS). The method is successfully applied to the design of a TSK-type fuzzy logic (FL) controller and a sliding mode-type (SM) controller for the uncertain nonlinear system of an inverted pendulum on a cart for large pole angles (+/-86 degrees). The resulting controller's performance compares favorably to others designed with cell mapping (CM) and a genetic algorithm (GA).