A fuzzy logic controller design methodology for 4D systems with optimal global performance using enhanced cell state space based best estimate directed search method

Best estimate directed search (BEDS) is a generalized automatic nonlinear controller optimization technique. The cell state space based dynamic programming is a simple approach to generating a good estimate of the optimal control table (OCT) even for high order systems, thus can be used by BEDS to generate an initial best estimate control surface resulting in fast convergence rate. Therefore, it would be ideal to integrate OCT and BEDS into a single tool. Furthermore, due to physical memory limit, cell state space of high order systems often has low cell resolution, which may also contribute to the slow convergence of fuzzy logic controller optimization. This paper also proposed a scheme to control the spatial distribution of training data in order to expedite the optimization procedure with low cell resolution. The approaches were tested on a 4D inverted pendulum system and showed great promises. A linear quadratic regulator is also presented for comparison.