Asynchronous model predictive control of LPV systems with stochastic communication protocol

IF 3.7 2区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Nonlinear Analysis-Hybrid Systems Pub Date : 2024-06-25 DOI:10.1016/j.nahs.2024.101522

Hongjie Pang , Jun Cheng , Huaicheng Yan , Dan Zhang , Wenhai Qi

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Abstract

This study is dedicated to exploring the challenge of asynchronous resilient robust model predictive control (RMPC) for linear parameter-varying (LPV) systems operating under a stochastic communication protocol (SCP). In contrast to the conventional Markov-based SCP, a novel sojourn probability-based SCP is introduced to regulate packet transmissions. This innovative approach simplifies the determination of transition probabilities and lessens the computational burden. Acknowledging the challenges associated with observing sojourn probability information, a mode detector is employed to describe the connection between mode discrepancies. To address parameter uncertainties, a novel detected-mode-based resilient control law is formulated to ensure the mean-square stability of the LPV system within the resilient RMPC framework. Additionally, an online algorithm for resilient RMPC is presented, grounded in an auxiliary optimization problem. Ultimately, the effectiveness of the proposed control strategy is validated via a high-purity distillation process model.

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带有随机通信协议的 LPV 系统异步模型预测控制

本研究致力于探索在随机通信协议（SCP）下运行的线性参数变化（LPV）系统的异步弹性鲁棒模型预测控制（RMPC）所面临的挑战。与传统的基于马尔可夫的 SCP 不同，本文引入了一种新颖的基于逗留概率的 SCP 来调节数据包传输。这种创新方法简化了过渡概率的确定，减轻了计算负担。考虑到观测瞬时概率信息所面临的挑战，我们采用了模式检测器来描述模式差异之间的联系。为解决参数不确定性问题，制定了一种基于检测模式的新型弹性控制法则，以确保 LPV 系统在弹性 RMPC 框架内的均方稳定性。此外，还提出了一种基于辅助优化问题的弹性 RMPC 在线算法。最后，通过高纯度蒸馏过程模型验证了所提控制策略的有效性。

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来源期刊

Nonlinear Analysis-Hybrid Systems AUTOMATION & CONTROL SYSTEMS-MATHEMATICS, APPLIED

CiteScore

8.30

自引率

9.50%

发文量

审稿时长

>12 weeks

期刊介绍： Nonlinear Analysis: Hybrid Systems welcomes all important research and expository papers in any discipline. Papers that are principally concerned with the theory of hybrid systems should contain significant results indicating relevant applications. Papers that emphasize applications should consist of important real world models and illuminating techniques. Papers that interrelate various aspects of hybrid systems will be most welcome.

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