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This article investigates the fault-tolerant fixed-time cooperative control problem for nonstrict-feedback nonlinear multiagent systems subject to error constraints and input saturation. Fuzzy logic systems are employed to deal with unknown nonlinear dynamics. By using adaptive technique and power integration technique, two barrier-function-based fixed-time control strategies are projected. In the first scheme, a novel adaptive fault-tolerant distributed fixed-time control protocol is developed. Besides, a new real-time compensation mechanism is proposed, where the compensation signal is provided if and only if there exists input saturation. Compared with the mechanisms for always compensating signals in existing results, the proposed real-time compensation mechanism may reduce energy consumption. In the second scheme, an adaptive fault-tolerant priority-based fixed-time control protocol is proposed, which may reduce the computational complexity arising from numerous neighbors’ variables. Both of the proposed two strategies can avoid the singular problem by constructing high-order derivable continuous functions. Besides, the developed control protocols can ensure the errors in MASs are practical fixed-time stable, meanwhile, the error constraints will not be violated in operation. Stability analysis and simulation results illustrate the effectiveness of the proposed strategies. [ABSTRACT FROM AUTHOR]

Summary: In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time‐delay systems with time‐varying full state constraints and input saturation. To overcome the problem of time‐varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov‐Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods. [ABSTRACT FROM AUTHOR]