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arXiv 2206.01700eess.SYcs.SY
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时变系统的双重自适应复合自适应控制

Composite Adaptive Control for Time-varying Systems with Dual Adaptation

Raghavv Goel, Sayan Basu Roy

摘要:

针对含有时变不确定参数的动力系统,提出了一种基于双自适应策略的复合自适应控制结构。虽然大多数文献中的自适应控制方案解决的情况下,恒定的参数,最近的研究已经概念化的改进自适应控制技术的时变系统的严格的稳定性证明。所提出的工作是朝着类似的方向努力,其中引入了一种新的双重自适应机制,以有效地解决参数的时变性质。投影和$σ$ -修改算法的策略相结合,使用的变量,索赔的跟踪误差空间的全局结果。虽然经典的自适应系统需要一个严格的条件的持续激励(PE)的精确参数估计,所提出的工作依赖于一个温和的条件,称为初始激励(IE)相同。严格的李雅普诺夫稳定性分析进行建立一致最终有界(UUB)稳定的闭环系统。进一步分析表明,所提出的工作可以恢复以前设计的基于IE的自适应控制器的性能的情况下,时不变系统。

英文摘要:

This paper proposes a composite adaptive control architecture using dual adaptation scheme for dynamical systems comprising time-varying uncertain parameters. While majority of the adaptive control schemes in literature address the case of constant parameters, recent research has conceptualized improved adaptive control techniques for time-varying systems with rigorous stability proofs. The proposed work is an effort towards a similar direction, where a novel dual adaptation mechanism is introduced to efficiently tackle the time-varying nature of the parameters. Projection and $σ$-modification algorithms are strategically combined using congelation of variables to claim a global result for the tracking error space. While the classical adaptive systems demand a restrictive condition of persistence of excitation (PE) for accurate parameter estimation, the proposed work relies on a milder condition, called initial excitation (IE) for the same. A rigorous Lyapunov stability analysis is carried out to establish uniformly ultimately bounded (UUB) stability of the closed-loop system. Further it is analytically shown that the proposed work can recover the performance of previously designed IE-based adaptive controller in case of time invariant systems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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