There are times where it's perfectly appropriate. 61603032 ) and in part by the Key Research and Development Program of Jiangxi Province, China ( Grant No. This work was supported in part by the National Science Foundation of China (Grant No. Key Research and Development Program of Jiangxi Province National Natural Science Foundation of China © 2021 Elsevier B.V.Īuthor keywords Adaptive control Barrier Lyapunov function Fixed-time control Indexed keywords Engineering controlled terms:Ĭontrollers Feedback control Lyapunov functions Navigation Nonlinear feedback Radial basis function networksĪdaptive Control Barrier lyapunov function Fixed time Fixed-time control Input saturation Pure-feedback system Time tracking Tracking control problem Tracking controls Tracking errorsĪrticle feedback system neighborhood radial basis function neural network simulation theoretical study The aforementioned problem can be solved using the proposed control method, and the simulation experiments indicate the effectiveness of the designed controller. Further, a theorem is proposed to ensure that the designed controller allows the system output to track the reference signal within a fixed time, ensuring that the tracking error is limited to a small neighborhood of origin within a fixed time and that all the signals in the system are bounded.
A combination of the fixed-time stability theory, barrier Lyapunov function, and radial basis function neural network is employed to develop the proposed method for obtaining the expected performance from the considered system. A sequence of auxiliary virtual and actual input signals is designed to obtain an expression for the system tracking error and stabilize the system. This paper considers the fixed-time tracking control problem for system-constrained nonlinear pure-feedback systems involving input saturation and output constraints.
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