Adaptive Fuzzy Control Based on Approximation Errors for Nonlinear Systems
Yuanwei Jing, Xinjiang Wei · Journal of Northeastern University · 2004
A stable adaptive fuzzy control method is proposed for a class of uncertain single input/output nonlinear systems, of which the state variables are estimated by designing a fuzzy state observer instead of the assumption that these variables need a full observability. Such unknown nonlinearities are approximated by the fuzzy logic systems on the key assumption that the approximation errors satisfy certain bounding conditions. Then, Lyapunov synthesis is used to analyse the fuzzy system to obtain the adaptive laws of corresponding parameters. Such an overall control systems can guarantee not only that the tracking error converges in a small neighborhood of zero but that all signals involved are uniformly bounded. Finally, a simulation example is given to testify the validity and efficiency of the proposed method.