Title :
DSC-backstepping based robust adaptive fuzzy control for a class of strict-feedback nonlinear systems
Author :
Li, Tieshan ; Feng, Gang ; Zou, Zaojian
Author_Institution :
State Key Lab. of Ocean Eng. & the Sch. of Naval Archit., Shanghai Jiao Tong Univ., Shanghai
Abstract :
A robust adaptive tracking control problem is discussed for a class of strict-feedback uncertain nonlinear systems. Takagi-Sugeno type fuzzy logic systems are used to approximate the uncertainties. A unified and systematic procedure is developed to derive a novel robust adaptive tracking controller by use of the input-to-state stability (ISS) and by combining the dynamic surface control (DSC)-based backstepping technique and generalized small gain approach. The key features of the algorithm are that, firstly, the problem of ldquoexplosion of complexityrdquo inherent in the conventional backstepping method is circumvented, secondly, the number of parameters updated on line for each subsystem is reduced dramatically to 2. These features result in a much simpler algorithm, which is convenient to realize in application. In addition, it is shown that all closed-loop signals are semi-global uniformly ultimately bounded (SGUUB). Finally, simulation results via an application example of a pendulum system with motor is used to demonstrate the effectiveness and performance of the proposed scheme.
Keywords :
adaptive control; closed loop systems; control nonlinearities; feedback; fuzzy control; nonlinear control systems; robust control; tracking; uncertain systems; DSC-backstepping method; ISS; SGUUB; Takagi-Sugeno type fuzzy logic systems; closed-loop signals; dynamic surface control; input-to-state stability; pendulum system; robust adaptive fuzzy control; robust adaptive tracking control problem; semi-global uniformly ultimately bounded; strict-feedback nonlinear systems; Adaptive control; Adaptive systems; Backstepping; Control systems; Fuzzy control; Nonlinear control systems; Nonlinear systems; Programmable control; Robust control; Robust stability;
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630536