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A new unmatched-disturbances compensation and fault-tolerant control for partially known nonlinear singular systems

机译:用于部分已知的非线性奇异系统的新无与伦比的扰动补偿和容错控制

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This study investigates the challenge of designing a fault-tolerant control (FTC) for partially known nonlinear singular systems subjected to unmatched uncertainties in addition to actuator and sensor faults. The suggested technique is dependent on the neural network-based adaptive observer. The unknown system nonlinearities are approximated by making use of an adaptive neural network (NN) approximation technique. The parameters of the NN are unknown. A new methodology is proposed to transform the partially known singular system to a non-singular form with unknown uncertainties. Different from all previous work dealing with singular systems with partially known system parameters, an adaptive observer is proposed with the help of adaptive laws to obtain an estimation of the augmented states of the constructed descriptor system. Based on the estimated states, a new approach for dealing with unmatched disturbances and faults are proposed. Finally, an adaptive controller is designed to account for unmatched disturbances and faults. The asymptotic stability of the overall system is guaranteed via Lyapunov-stability functional. The designed method is applied efficiently to a satellite control system as a practical example in addition to another numerical example. (C) 2020 ISA. Published by Elsevier Ltd. All rights reserved.
机译:本研究研究除了执行器和传感器故障之外,还研究了针对未经匹配的不确定性的部分已知的非线性奇异系统设计容错控制(FTC)的挑战。建议的技术取决于基于神经网络的自适应观察者。通过利用自适应神经网络(NN)近似技术,通过利用自适应神经网络(NN)近似技术来近似未知的系统非线性。 NN的参数是未知的。提出了一种新的方法来将部分已知的奇异系统转变为具有未知不确定性的非单数形式。与具有部分已知的系统参数的奇异系统的所有先前的工作不同,在自适应法律的帮助下提出了一种自适应观察者,以获得构造描述符系统的增强状态的估计。基于估计的国家,提出了一种处理无与伦比的干扰和故障的新方法。最后,自适应控制器旨在考虑无与伦比的干扰和故障。通过Lyapunov-稳定功能保证整个系统的渐近稳定性。除了另一个数值示例之外,设计的方法是作为实际示例的作为实际示例的卫星控制系统。 (c)2020 ISA。 elsevier有限公司出版。保留所有权利。

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