Adaptive fuzzy controller design for a class of uncertain nonlinear MIMO systems

Abstract

A combined adaptive fuzzy output feedback control scheme is presented for a class of multipleinput-multiple-output (MIMO) nonlinear systems with the unmeasured states. A state observer is used to estimate the unmeasured states of the systems. The resulting closed-loop system consists of the state observer and four control components, where the control components are the combined adaptive fuzzy controller, supervisory controller, H ∞ robust control item and auxiliary compensation item. Compared with the existing results in the observer design, the main advantages of this scheme are that (1) the combined adaptive fuzzy control item, which can trade off the fuzzy descriptions for controlled object rules and control action rules, is designed in the controller; (2) the proposed controller has the supervisory control performance. The stability of the closed-loop system is analyzed by using Lyapunov analysis method. Simulation results validate the effectiveness of the proposed control scheme.

Adaptive neural network tracking control of robot manipulators with prescribed performance

“…In papers [5][6][7], the estimated inertia matrixĜ(x) is assumed to be always nonsingular without providing any proof to the validity of this assumption when the parameters of the approximator are updated. In reference [8], only the diagonal elements of G(x) are approximated, and the updating laws guarantee the regularity ofĜ(x).…”

Intelligent tracking control of a DC motor driver using self-organizing TSK-type fuzzy neural networks

“…However, a trade-off problem between chattering and control accuracy arises. To attack this problem reducing the chattering phenomenon, several compensators were studied [15][16][17][18]. Wu et al [15] presented a smooth compensator to guarantee system stable; however, the tracking error can exponentially converge to a small neighborhood of the trajectory command.…”

“…Hsu et al [16] proposed a fuzzy compensator to completely remove the chattering phenomena; however, the adaptive law will make it go to infinity. Some researchers combined the robust control approach to remove the influence of the external disturbance and approximation error in [17,18]. However, the control effort may lead to a large control signal as a specified attenuation level is chosen small.…”