Adaptive Prescribed‐Time Tracking Control of Time‐Varying Uncertain Nonlinear Systems Using Neural Networks

ABSTRACT In this article, we develop an adaptive prescribed‐time control method for time‐varying uncertain nonlinear systems. The method relaxes the assumptions in existing works on adaptive control of time‐varying uncertain nonlinear systems. The ideal approximation property of neural networks (NNs) is utilized in controller design, but its parameters are not involved in the calculation of adaptive laws. In addition, a class of prescribed‐time turning functions is constructed to guarantee the prescribed‐time convergence. The proposed method ensures that all signals are bounded and the tracking error can converge to a small neighborhood of zero at a user prescribed time. Finally, we provide two examples to verify the proposed control method.