Soft-Target-Based Predictive Fuzzy Control for a Cart-Pendulum System with Dynamic Constraints
Yougen Chen and Seiji Yasunobu
Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Human decisions to act are based on broad targets and respond flexibly in different situations. Such, self-adaptation to dynamic constraints is difficult but important for autonomous control. Conventional control usually uses a single target that results in inflexibility in responding to dynamic environments such as changes in constraints. We propose a predictive fuzzy intelligent controller based on soft targets defined as a series of target sets that include many target elements with different satisfaction grades and are converted to target setting knowledge by fuzzy logic. This controller was applied to upswing and stabilization control of a cart-pendulum system with dynamic changing limit positions as constraints to realize situational self-adaptation and target self-regulation. Simulation and experiments demonstrated the feasibility of our soft-target-based intelligent controller.
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