Decentralized tracking control design based on intelligent critic for an interconnected spring-mass-damper system

Wenqian Fan, Aohua Liu, Ding Wang
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引用次数: 0

Abstract

In this paper, the decentralized tracking control (DTC) problem is investigated for a class of continuous-time nonlinear systems with external disturbances. First, the DTC problem is resolved by converting it into the optimal tracking controller design for augmented tracking isolated subsystems (ATISs). %It is investigated in the form of the nominal system. A cost function with a discount is taken into consideration. Then, in the case of external disturbances, the DTC scheme is effectively constructed via adding the appropriate feedback gain to each ATIS. %Herein, we aim to obtain the optimal control strategy for minimizing the cost function with discount. In addition, utilizing the approximation property of the neural network, the critic network is constructed to solve the Hamilton-Jacobi-Isaacs equation, which can derive the optimal tracking control law and the worst disturbance law. Moreover, the updating rule is improved during the process of weight learning, which removes the requirement for initial admission control. Finally, through the interconnected spring-mass-damper system, a simulation example is given to verify the availability of the DTC scheme.
基于智能评价的互联弹簧-质量-阻尼系统分散跟踪控制设计
研究了一类具有外部扰动的连续非线性系统的分散跟踪控制问题。首先,将DTC问题转化为增强跟踪隔离子系统(atis)的最优跟踪控制器设计,解决了DTC问题。它是以标称制的形式进行研究的。考虑一个带有折扣的成本函数。然后,在外部干扰的情况下,通过向每个ATIS添加适当的反馈增益,有效地构建了DTC方案。在此,我们的目标是获得最小化带有折扣的成本函数的最优控制策略。此外,利用神经网络的逼近特性,构造了求解Hamilton-Jacobi-Isaacs方程的批评网络,从而推导出最优跟踪控制律和最坏干扰律。并且在权值学习过程中改进了更新规则,消除了初始准入控制的要求。最后,通过弹簧-质量-阻尼器互联系统的仿真实例,验证了DTC方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.70
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