模块化鲁棒模型预测控制

F. T. Attarwala
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引用次数: 0

摘要

提出了一种将模型预测控制与明确定义的稳定性准则相结合的方法,以提高系统的鲁棒性能。稳定性准则在其基础上是基本的,可以普遍适用于任何规模的过程。稳定性判据是基于自变量的,可用于线性或非线性过程;当用于线性过程时,它具有准线性最优闭环特性。稳定性准则决定了优化的速度。制动动作可以与稳定性标准一起包含,以允许包括启动,正常操作和关闭在内的完整循环控制。稳定性标准一致地支持分层和分布式MPC实现;它允许在一个过程中形成一个分层和分布式的MPC系统,同时允许它连接到相邻的过程,作为整个生产链的统一控制系统的一部分,涉及模块化鲁棒MPC网络。从本质上讲,稳定性准则使MPC具有鲁棒性和模块化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modular robust model predictive control
This paper presents a method of combining model predictive control (MPC) with explicitly defined stability criteria for improved robust performance. The stability criteria is fundamental in its basis and can be applied universally to a process of any size. The stability criteria is independent variables based and can be used with linear or non-linear process; when used with linear process it imparts a quasi-linear optimal closed loop behavior. The stability criteria determines speed of optimization. A braking action can be included in conjunction with the stability criteria to permit a complete cycle control involving startup, normal operation and shutdown. The stability criteria supports both hierarchical and distributed MPC implementation consistently; that allows for the formation of a hierarchical and distributed MPC system within a process while permitting it to be connected to neighboring processes as part of a unified control system for an entire production chain involving a network of modular robust MPCs. Intrinsically, the stability criteria makes a MPC both robust and modular.
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