Overlapping-Horizon MPC: A Novel Approach to Computational Constraints in Real-Time Predictive Control

A. Leva, S. Formentin, Silvano Seva
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引用次数: 2

Abstract

Model predictive control (MPC) represents the state of the art technology for multivariable systems subject to hard signal constraints. Nonetheless, in many real-time applications MPC cannot be employed as the minimum acceptable sampling frequency is not compatible with the computational limits of the available hardware, i.e., the optimisation task cannot be accomplished in one sampling period. In this paper we generalise the classical receding-horizon MPC rationale to the case where n > 1 sampling intervals are required to compute the control trajectory. We call our scheme Overlapping-horizon MPC – OH-MPC for short – and we numerically show its attitude at providing a tunable trade-off between optimisation quality and real-time capabilities. 2012 ACM Subject Classification Computer systems organization → Real-time systems; Information systems → Process control systems
重叠视界MPC:实时预测控制中计算约束的新方法
模型预测控制(MPC)代表了受硬信号约束的多变量系统的最新技术。然而,在许多实时应用中,MPC不能被采用,因为最小可接受的采样频率与可用硬件的计算限制不兼容,也就是说,优化任务不能在一个采样周期内完成。在本文中,我们将经典的后退视界MPC理论推广到需要n > 1个采样间隔来计算控制轨迹的情况。我们称我们的方案为重叠视界MPC(简称OH-MPC),我们用数字表明了它在优化质量和实时能力之间提供可调权衡的态度。2012 ACM学科分类计算机系统组织→实时系统;信息系统→过程控制系统
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