具有非线性不确定性的描述符半马尔可夫跳跃系统的主动干扰减少方案

S. Mohanapriya, S. Harshavarthini
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引用次数: 0

摘要

通过使用主动干扰减少策略,本研究解决了描述符半马尔可夫跳跃系统在未知非线性不确定性(UNC)和非周期性干扰下的跟踪问题。与之前的研究不同,本研究将改进的等效输入干扰(IEID)估计器与广义修正重复控制(GMRC)规则相结合。为此,首先提出了 GMRC 的状态空间模型。然后,设计基于 IEID 估计器的复合 GMRC 来调节 UNC 和干扰,并确保所提模型的理想输出跟踪性能。通过构建增强的 Lyapunov-Krasovskii 函数,提出了以线性矩阵不等式保证闭环动力学均方渐近可接受性的充分条件。最后,利用推导出的充分条件验证了具有两种模式的直流电机结构的动力学。仿真和比较结果证实,与现有方法相比,该方法具有更好的跟踪性能。
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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Active disturbance reduction scheme for descriptor semi-Markovian jump systems with nonlinear uncertainties

By using an active disturbance reduction strategy, the current study addresses the tracking problem of descriptor semi-Markovian jump systems against unknown nonlinear uncertainties (UNC) and aperiodic disturbances. In contrast to previous studies, the improved equivalent-input-disturbance (IEID) estimator is merged with the generalized modified repetitive control (GMRC) rule. To do this, initially, the state-space model of GMRC is proposed. Then, the composite IEID estimator-based GMRC is designed to regulate UNC and disturbances and ensures desired output tracking performance of the proposed model. By constructing augmented Lyapunov–Krasovskii functional, sufficient conditions are presented to guarantee mean-square asymptotic admissibility of closed-loop dynamics in terms of linear matrix inequalities. Finally, the dynamics of DC motor structure with two modes are validated with derived sufficient conditions. The simulation and comparison results confirmed the better tracking performances over the existing methods.

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