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Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay

机译:在参数,非参数不确定性和随机控制信号延迟存在下完全模型的自由自适应控制

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摘要

In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided. (C) 2018 ISA. Published by Elsevier Ltd. All rights reserved.
机译:在本文中,开发了一种自适应控制器,用于离散时间线性系统,其考虑参数不确定度,内部外部非参数随机不确定性和时变控制信号延迟。另外,所提出的自适应控制设计以这样的方式,即它完全是无模型的。尽管这些属性在文献中分别进行了研究,但它们在适应性控制文献中并未结合在一起。 Q函数用于估计所提出的自适应控制器的长期性能。基于长期预测值生成控制策略,此策略搜索不确定和不稳定系统的最佳稳定控制信号。衍生的控制法不需要初始稳定控制假设,如最近文献中的初始稳定控制假设。分析了学习误差,控制信号收敛,最小化Q函数和瞬时奖励,以展示所提出的自适应控制器在仿真环境中的稳定性和有效性。最后,提供了对学习和控制信号的参数融合的关键见解。 (c)2018 ISA。 elsevier有限公司出版。保留所有权利。

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