Control of Inverted Pendulum and Vehicle Path Planning by Constraint-Interval Fuzzy Inference

Abstract

New perspective and treatment of fuzziness are introduced based on constraint-oriented ways of problem solving, by which two fundamental aspects of fuzziness, i.e., the “logical & hard” aspect and the “distributed & soft” aspect are elucidated. It is shown by using the control of inverted pendulum that the latter aspect provides flexible and efficient ways of problem solving, and also by using a path planning of a vehicle that the former aspect provides ways of constructing hybrid problem solving systems in which the symbolic problem solving methods in artificial intelligence can be incorporated to fuzzy logic-based information processing, thus enabling complicated and multi-step fuzzy inference.