Globally Stable Adaptive Fuzzy Control for Strict-feedback Nonlinear Systems

Abstract

A new adaptive fuzzy controller for uncertain based backstepping controller have enlarged the class of strict-feedback nonlinear systems is proposed. All the previous nonlinear systems that can be applicable. However, there are approximator-based adaptive control algorithms for the strict-some problems in the previous adaptive approximator-based feedback nonlinear systems are based on backstepping scheme controllers based on backstepping design method. First, some and guarantee semi-global closed-loop system stability. This paper proposes a new globally stabilizing adaptive fuzzy controller very tedious and complex analysis iS needed to determine for strict-feedback nonlinear system without backstepping. To regression matrices, virtual controls and their time derivatives. this end, an online self-structuring adaptive fuzzy system is The complexity exhibits an exponential increase progression as employed. The proposed adaptive fuzzy controller is considerably the dynamic order of the controlled system grows. In [18], this simpler than the previous ones based on backstepping. Only one FLS is employed to approximate a lumped uncertain nonlinearity, problem is overcome by viewing the original control problem which highlights the simplicity of our proposed control scheme. of the strict-feedback system as that of a normal system.Second, all the previous controllers guarantee the stability of

Observer-based robust adaptive fuzzy controller for strict-feedback nonlinear uncertain systems

“…Moreover, the original strict-feedback nonlinear system subject to the uncertainties, which is different from the previous result [9], can be transformed into the normal form of an equivalent system by means of the concept of Lie derivative. Fuzzy logic systems and some appropriate adaptive laws are used to approximate the unknown nonlinear functions and the unknown upper bounds of uncertainties.…”

“…In [6][7][8], the backstepping scheme was proposed to deal with the strict-feedback nonlinear systems, but it was a very tedious and complex task to determine the regression matrices, virtual controls and their time derivatives. Therefore, in order to overcome the aforementioned problem, this paper will adopt the technique of feedback linearization, which was presented in [9,10], to transform the original strictfeedback nonlinear system into the normal system.…”

“…It implies that the elements of the output tracking error vector cannot be obtain completely. Therefore, the concept of the high-gain observer [9,[26][27][28] and the technique of the state variable filters [22] are included in this paper to cope with the above undesirable characteristics.…”