Approximate model reference adaptive mechanism for nominal gain design of fuzzy control system

The difficult design of fuzzy logic control (FLC) can be processed in two separate stages: nominal design and optimal adjustment. The nominal design intends to figure out the nominal model of FLC including rule base, membership functions (MF's), and scaling gains. Different parameters require different design methods. A quantitative approach is presented in this paper to design the nominal scaling gain by using the idea of classical adaptive control. This adaptive mechanism requires only an approximate reference model of the plant, but it tolerates much more system uncertainties due to the inherent nonlinear feature of FLC. In reality, a first-order linear model is usually sufficient for achieving a reasonable performance. This approximate model reference based adaptive fuzzy control system is more robust than its classical counterpart in complex environment without deteriorating the original system stability. Therefore, it is an effective method to determine proper scaling gains for FLC.