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首页> 外文期刊>Optimal Control Applications and Methods >Single network adaptive critic aided dynamic inversion for optimal regulation and command tracking with online adaptation for enhanced robustness
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Single network adaptive critic aided dynamic inversion for optimal regulation and command tracking with online adaptation for enhanced robustness

机译:单网络自适应评论家辅助动态反演,用于最佳调节和命令跟踪,在线自适应,可增强鲁棒性

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摘要

To combine the advantages of both stability and optimality-based designs, a single network adaptive critic (SNAC) aided nonlinear dynamic inversion approach is presented in this paper. Here, the gains of a dynamic inversion controller are selected in such a way that the resulting controller behaves very close to a presynthesized SNAC controller in the output regulation sense. Because SNAC is based on optimal control theory, it makes the dynamic inversion controller operate nearly optimal. More important, it retains the two major benefits of dynamic inversion, namely (i) a closed-form expression of the controller and (ii) easy scalability to command tracking applications without knowing the reference commands a priori. An extended architecture is also presented in this paper that adapts online to system modeling and inversion errors, as well as reduced control effectiveness, thereby leading to enhanced robustness. The strengths of this hybrid method of applying SNAC to optimize an nonlinear dynamic inversion controller is demonstrated by considering a benchmark problem in robotics, that is, a two-link robotic manipulator system.
机译:为了结合基于稳定性和基于最优性的设计的优点,本文提出了一种基于单网络自适应评论家(SNAC)的非线性动态反演方法。在此,以这样的方式选择动态反相控制器的增益,使得所得的控制器在输出调节意义上表现得非常接近于预先合成的SNAC控制器。由于SNAC基于最优控制理论,因此它使动态逆变器控制器几乎处于最佳状态。更重要的是,它保留了动态反转的两个主要优点,即(i)控制器的闭式表达式和(ii)无需跟踪先验命令就可以轻松扩展到命令跟踪应用程序。本文还提出了一种扩展的体系结构,该体系结构可在线适应系统建模和反演错误,并降低控制效果,从而提高鲁棒性。通过考虑机器人技术中的基准问题(即双链机器人机械手系统),证明了这种应用SNAC来优化非线性动态逆变器的混合方法的优势。

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