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Prescribed finite-time adaptive tracking control for a class of full state constrained non-strict feedback nonlinear multi-agent systems
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Prescribed finite-time adaptive tracking control for a class of full state constrained non-strict feedback nonlinear multi-agent systems
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Journal Article
Prescribed finite-time adaptive tracking control for a class of full state constrained non-strict feedback nonlinear multi-agent systems
2025
Overview
The goal of this paper is to discuss the prescribed finite-time tracking control issue for uncertain full state constrained non-strict feedback nonlinear multi-agent systems (MASs). In the framework of backstepping design, a novel practical virtual control signal is constructed based on hyperbolic tangent function. The design of practical virtual control signal can not only satisfy the same constraints as the corresponding state variables, but also successfully avoid singularity problem. Furthermore, a prescribed finite-time control protocol is proposed on the basis of an improved universal barrier Lyapunov function (UBLF) approach and radial basis function neural network (RBF NN) technique. By the aid of the developed UBLF, the proposed control scheme enables the MAS to complete synchronization objective within an explicitly predetermined settling time and with an error accuracy given by the designer. Based on the stability theorem, it has been theoretically proven that the proposed control protocol can guarantee the MAS achieves synchronous tracking within a pre-given finite time while avoiding violation of the full state constraints. Finally, two numerical simulation examples are provided to further demonstrate the efficacy of the proposed control strategy. By comparing the control effectiveness with previous results, it is found that the convergence rate of the MAS is improved, and all the state variables can be restricted to the constraints throughout the entire control process.
Publisher
Springer Netherlands,Springer Nature B.V
