Search

This article proposes a fuzzy adaptive output feedback control method for multi-agent systems with uncertainties and nonlinearities, considering both full state constraints and unmeasurable states. Aiming at the problem that the state of followers in nonlinear multi-agent systems is unmeasured, an observer is constructed by applying the characteristics of fuzzy logic systems to achieve the output feedback control scheme. The state constraint of multi-agent systems is also a great challenge. Based on a backstepping technique and integral barrier Lyapunov functions (iBLFs), all states are constrained, and an adaptive controller is designed. Compared with imposing constraints on the error and then constraining the state, the method in this article compensates for defects in the constraint conditions. Furthermore, under the Lyapunov stability theorem, we can prove that all signals of closed-loop systems are cooperative semi-global uniformly ultimately bounded (CSUUB). A simulation validates the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Abstract: An adaptive fuzzy control approach is proposed for a class of multiple-input–multiple-output (MIMO) nonlinear systems with completely unknown nonaffine functions. The MIMO systems are composed of n subsystems and each of subsystems is in the nested lower triangular form. It is difficult and complicated to control this class of systems due to the existence of unknown nonaffine functions and the couplings among the nested subsystems. This difficulty is overcome by introducing some special type Lyapunov functions and taking advantage of the mean-value theorem, the backstepping design method and the approximation property of the fuzzy systems. The proposed control approach can guarantee that all the signals in the closed-loop system are bounded. A simulation experiment is utilized to verify the feasibility of the proposed approach. [Copyright &y& Elsevier]