Indirect Adaptive Fuzzy H∞ Tracking Control with Self-Structuring Algorithm for a Class of Uncertain Nonlinear SISO Systems

Indirect adaptive fuzzy controller with a self-structuring algorithm is proposed in this paper to achieve tracking performance for a class of uncertain nonlinear single-input single-output (SISO) systems with external disturbances. Selecting membership functions and the fuzzy rules are difficult in fuzzy controller design. As a result, self-structuring algorithm is used in this paper, which simplifies the design of fuzzy controller. Lyapunov analysis is used to prove asymptotic stability of the proposed approach. Application of the proposed control scheme to a second-order inverted pendulum system demonstrates the effectiveness of the proposed approach.

Optimal Robust Adaptive FuzzyH∞Tracking Control without Reaching Phase for Nonlinear System

An optimalH∞tracking-based indirect adaptive fuzzy controller for a class of perturbed uncertain affine nonlinear systems without reaching phase is being developed in this paper. First a practical Interval Type-2 (IT2) fuzzy system is used in an adaptive scheme to approximate the system using a nonlinear model and to determine the optimal value of theH∞gain control. Secondly, to eliminate the trade-off betweenH∞tracking performance and high gain at the control input, a modified output tracking error has been used. The stability is ensured through Lyapunov synthesis and the effectiveness of the proposed method is proved and the simulation is also given to illustrate the superiority of the proposed approach.

Indirect Adaptive Fuzzy Controller for LEGO Mindstorms NXT Two-Wheeled Robot

An indirect adaptive fuzzy controller is proposed to control the LEGO Mindstorms NXT Two-Wheeled robot in this paper. The dynamical model of the robot, LEGO Mindstorms NXT, is derived from Lagrange of kinetic and potential energies. Based on the developed model, two fuzzy systems are first used to approximate the grey functions in the developed model, and then the adaptive fuzzy controller is designed. Adaptation laws for the above fuzzy systems are derived from the Lyapunov stability analysis. According to the stability analysis, the developed control system guarantees that the system tracking performance and the error convergence can be assured in the closed-loop system. Finally, we apply the proposed fuzzy controller to balance the LEGO Mindstorms NXT two-wheeled robot.