Output consensus for interconnected systems via the internal model principle and a model predictive control based strategy

IF 3.9 2区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Ye Zhang , Fei Li , Dongya Zhao , Xing-Gang Yan , Sarah K. Spurgeon
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引用次数: 0

Abstract

Interconnected systems are commonly found in process networks. In this paper, an output consensus framework is proposed for a class of continuous interconnected linear heterogeneous systems subject to constraints. A distributed output consensus control strategy is developed by combining the internal model principle (IMP) with model predictive control (MPC). A distributed iterative algorithm is designed to solve the IMP conditions for interconnected systems. The IMP based control plays two main roles: On the one hand, it helps to deal with the interconnection effects existing between the subsystems; on the other hand, it drives the subsystems to track the reference dynamics in order to achieve output consensus. The MPC determines an optimized control gain while being able to handle constraints. Simulation examples and experimental trials are presented to validate the effectiveness and superiority of the proposed method.
基于内模原理和模型预测控制策略的互联系统输出一致性
相互连接的系统通常出现在过程网络中。本文提出了一类具有约束的连续互联线性异构系统的输出一致性框架。将内模原理(IMP)与模型预测控制(MPC)相结合,提出了一种分布式输出一致性控制策略。设计了一种分布式迭代算法来求解互联系统的IMP条件。基于IMP的控制主要有两个作用:一方面,它有助于处理子系统之间存在的互连效应;另一方面,它驱动子系统跟踪参考动态,以达到输出一致性。MPC在能够处理约束条件的同时确定了优化的控制增益。通过仿真算例和实验验证了该方法的有效性和优越性。
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来源期刊
Journal of Process Control
Journal of Process Control 工程技术-工程:化工
CiteScore
7.00
自引率
11.90%
发文量
159
审稿时长
74 days
期刊介绍: This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. In addition to the traditional chemical processing and manufacturing applications, the scope of process control problems involves a wide range of applications that includes energy processes, nano-technology, systems biology, bio-medical engineering, pharmaceutical processing technology, energy storage and conversion, smart grid, and data analytics among others. Papers on the theory in these areas will also be accepted provided the theoretical contribution is aimed at the application and the development of process control techniques. Topics covered include: • Control applications• Process monitoring• Plant-wide control• Process control systems• Control techniques and algorithms• Process modelling and simulation• Design methods Advanced design methods exclude well established and widely studied traditional design techniques such as PID tuning and its many variants. Applications in fields such as control of automotive engines, machinery and robotics are not deemed suitable unless a clear motivation for the relevance to process control is provided.
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