首页|Neural network based adaptive nonsingular practical predefined-time fault-tolerant control for hypersonic morphing aircraft
Neural network based adaptive nonsingular practical predefined-time fault-tolerant control for hypersonic morphing aircraft
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This paper develops a novel Neural Network(NN)-based adaptive nonsingular practical predefined-time controller for the hypersonic morphing aircraft subject to actuator faults.Firstly,a novel Lyapunov criterion of practical predefined-time stability is established.Following the pro-posed criterion,a tangent function based nonsingular predefined-time sliding manifold and the con-trol strategy are developed.Secondly,the radial basis function NN with a low-complexity adaptation mechanism is incorporated into the controller to tackle the actuator faults and uncer-tainties.Thirdly,rigorous theoretical proof reveals that the attitude tracking errors can converge to a small region around the origin within a predefined time,while all signals in the closed-loop sys-tem remain bounded.Finally,numerical simulation results are presented to verify the effectiveness and improved performance of the proposed control scheme.
Hypersonic morphing air-craft(HMA)Neural network(NN)Adaptive controlPractical predefined-time controlFault-tolerant control
Shihao XU、Changzhu WEI、Litao ZHANG、Rongjun MU
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School of Astronautics,Harbin Institute of Technology,Harbin 150001,China
Beijing Institute of Control & Electronics Technology,Beijing 100038,China
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