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This paper presents an optimized feedforward Takagi-Sugeno type fuzzy logic controller (FLC) design methodology for 4D systems. The method interpolates a cell space based optimal control table to generate optimal trajectories. A FLC is tuned using the sampling data from the optimal trajectories. In this way, the effect of cell mapping error in the FLC tuning is greatly reduced even with very low cell resolution. The optimized feedforward design is further combined with the best estimate directed search, a feedback iterative FLC optimization technique, to expedite the convergence of the optimization procedure. A 4D inverted pendulum case is simulated to justify the methodologies.