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A Decentralized Event-Based Model Predictive Controller Design Method for Large-Scale Systems

机译:大规模系统的基于事件的分散模型预测控制器设计方法

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This paper presents a new methodology to design decentralized event-based control strategy for large-scale systems under the general MPC framework. The method introduces an appealing perspective to effectively reduce the computing load and communication effort in computer-based networks by incorporating the MPC approach in an event-based design framework. The proposed methodology is shown to be capable of coping explicitly with multi-input, multi-output (MIMO) plants having constraints while preserving the control performance characteristics due to decentralized MPC method with less control computational effort. The proposed control architecture ensures the stability of the closed-loop system, optimal performance and significant reduction in computational load without sacrificing the performance. Performances of the proposed method are comparatively explored on a catalytic alkylation of benzene process plant as the benchmark case study. A diverse set of experiments has been conducted to clearly demonstrate superiority of the proposed methodology compared to the standard time-driven decentralized MPC scheme on the basis of mean-squared error and number of events or control actions measures.
机译:本文提出了一种在通用MPC框架下为大型系统设计基于分散事件的控制策略的新方法。该方法引入了一种有吸引力的观点,即通过将MPC方法合并到基于事件的设计框架中,可以有效地减少基于计算机的网络中的计算负载和通信工作量。所提出的方法被证明能够显式地应对具有约束的多输入多输出(MIMO)设备,同时由于分散的MPC方法而以较少的控制计算工作来保持控制性能特征。所提出的控制体系结构可确保闭环系统的稳定性,最佳性能并在不牺牲性能的情况下显着减少计算负荷。以苯加工厂的催化烷基化为例,比较研究了该方法的性能。根据均方误差和事件数或控制措施,已进行了一系列实验以清楚证明所提出的方法与标准时间驱动的分散式MPC方案相比的优越性。

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