Adapting the gain of an FLC with genetic algorithms

摘要: Abstract Fuzzy logic controllers are knowledge-based systems, incorporating human knowledge into their base through fuzzy rules and membership functions. The definition of these functions is generally affected by subjective decisions, having a great influence over the performance controller. In some cases, defined within normalized interval, includes set scaling to convert input variables from its real value one, outputs value. Different works have proposed application genetic strategies, with learning purpose, FLCs. usually centered on and/or rule base, using fixed (predefined) this paper, evolution applied modify gain controller (by modifying function each or output variable), base. use linear nonlinear analyzed.