Adaptive Control foraClass ofNonaffine Systems BasedonFuzzy-Neural Approach

An adaptive control design methodisproposed fora class ofuncertain single-input single-output (SISO) nonaffine systembasedonfuzzy-neural approach. Tothe authors' knowledge, thiscontrolproblemis firstly considered inthis paper. Itisconsidered difficult tobedealt withinthecontrol literature, mainly because thatthevirtual controls andthefinal control lawofuncertain nonaffine system arenoteasytoresolve. Toovercome thisdifficulty, thefuzzy-neural approximator cancels theunknownpartof theinverse functions adaptively. Then,Inverse design, backstepping design, andfeedback linearization techniques areincorporated todealwiththis problem. Itisproved that thewholeclosed-loop systemisstable inthesenseof Lyapunov. The control performance isguaranteed by suitably choosing thedesign parameters. Simulation study was included to demonstrate theeffectiveness ofthe proposed method.