3DoF-KF HMPC: A Kalman filter-based Hybrid Model Predictive Control Algorithm for Mixed Logical Dynamical Systems

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice Pub Date : 2024-11-21 DOI:10.1016/j.conengprac.2024.106171

Owais Khan , Mohamed El Mistiri , Sarasij Banerjee , Eric Hekler , Daniel E. Rivera

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Abstract

This paper presents the formulation, design procedure, and application of a hybrid model predictive control (HMPC) scheme for hybrid systems that is embedded in a mixed logical dynamical (MLD) framework. The proposed scheme adopts a three degrees-of-freedom (3DoF) tuning method to accomplish precise setpoint tracking and ensure robustness in the face of disturbances (both measured and unmeasured) and uncertainty. Furthermore, the HMPC algorithm employs setpoint and disturbance anticipation to proactively enhance controller performance and potentially reduce control effort. Slack variables in the objective function prevent the mixed-integer quadratic problem from becoming infeasible. The effectiveness of the proposed algorithm is demonstrated through its application in three distinct case studies, which include control of production–inventory systems, time-varying behavioral interventions for physical activity, and management of epidemics/pandemic prevention. These case studies indicate that the HMPC algorithm can effectively manage hybrid dynamics, setpoint tracking and disturbance rejection in diverse and demanding circumstances, while tuned to perform well in the presence of nonlinearity and uncertainty.

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3DoF-KF HMPC：基于卡尔曼滤波器的混合逻辑动态系统混合模型预测控制算法

本文介绍了嵌入混合逻辑动力学（MLD）框架的混合系统混合模型预测控制（HMPC）方案的制定、设计过程和应用。所提出的方案采用三自由度（3DoF）调整方法来实现精确的设定点跟踪，并确保在面对干扰（测量到的和未测量到的）和不确定性时的鲁棒性。此外，HMPC 算法还采用了设定点和干扰预测，以主动提高控制器性能，并有可能减少控制工作量。目标函数中的松弛变量可防止混合整数二次方问题变得不可行。通过在三个不同案例研究中的应用，证明了所提算法的有效性，这三个案例研究包括生产-库存系统的控制、针对体育活动的时变行为干预以及流行病/大流行病预防管理。这些案例研究表明，HMPC 算法可以在各种苛刻的环境下有效地管理混合动力学、设定点跟踪和干扰抑制，同时还能在非线性和不确定性的情况下保持良好的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Control Engineering Practice 工程技术-工程：电子与电气

CiteScore

9.20

自引率

12.20%

发文量

183

审稿时长

44 days

期刊介绍： Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper. The scope of Control Engineering Practice matches the activities of IFAC. Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.