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In this paper, an adaptive fixed-time output feedback formation control problem is investigated for nonlinear multi-agent systems with a nonstrict-feedback structure. In the controller design procedure, the neural network state observer is designed to estimate the unmeasurable state variables. Dynamic surface control (DSC) technique is applied to avoid the repeated differentiation for the virtual control signals. The dynamic surface compensation signals can realise the practical fixed-time bounded. Utilising the classified discussion method, the difficulty of controller design caused by the existence of observer error term is addressed. The technique of transformation of the index set is employed to cope with the related variables of the neighbour states, which simplifies the controller design. Under the presented control mechanism, all closed-loop signals remain bound for a fixed period of time, the formation control performance target between all followers and leader can be achieved. And the formation errors and state observers errors are both bounded such that can converge to a little domain around zero. Simulation results are provided to test the availability of the presented strategy.

Adaptive fixed-time output feedback formation control for nonstrict-feedback nonlinear multi-agent systems