FC⁴ fuzzy rules system acquisition of complex system using interactive evolutionary computation

Ideal fuzzy rules systems are supposed to be flexible, complete, consistent, compact and comprehensible (FC⁴). This paper describes the use of the interactive genetic algorithms (IGAs) to acquire FC⁴ fuzzy rules of complex system. The fuzzy sets of fuzzy rules are explained with the linguistic expressions through comparing with the standard linguistic variables. It is helpful to make the fuzzy rules to be comprehensible and conduct human evaluation during IGAs process. Not only quantitative evaluation but qualitative one is used to evaluate both the interpretability and control performance of the acquired fuzzy rules. The presented approach is applied to the control of the non-linear and coupled system with two control objectives. Simulation experiments show that the approach is feasible to acquire the FC ⁴ fuzzy rules with good interpretability and good control performance.