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:应用于体育活动的优化干预。

Owais Khan, Mohamed El Mistiri, Daniel E Rivera, César A Martin, Eric Hekler
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引用次数: 0

摘要

混合模型预测控制(Hybrid Model Predictive Control,简称 HMPC)是一种决策工具,用于新颖的行为干预,以增加久坐不动的成年人的体育锻炼,如 "快走"(Just Walk)。本文针对与行为医学问题相关的混合逻辑动力学(MLD)系统开发了一种基础广泛的混合模型预测控制(HMPC)公式,并在 "健步走 "研究中产生的代表性参与者模型上进行了说明。MLD 模型是根据达到每日步数目标给予积分的要求和分类输入变量开发的。该算法具有三个自由度调整功能,用于设定点跟踪、测量和非测量干扰抑制,从而提高了控制器的鲁棒性;干扰预测进一步提高了即将发生的事件(如周末和天气预报)的性能。为避免相应的混合整数二次问题(MIQP)变得不可行,在目标函数中引入了松弛变量。仿真结果表明,所提出的 HMPC 方案能有效管理混合动力、设定点跟踪、干扰抑制以及干预两个阶段(启动和维护)之间的过渡,适合在临床试验中进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Kalman filter-based Hybrid Model Predictive Control Algorithm for Mixed Logical Dynamical Systems: Application to Optimized Interventions for Physical Activity.

Hybrid Model Predictive Control (HMPC) is presented as a decision-making tool for novel behavioral interventions to increase physical activity in sedentary adults, such as Just Walk. A broad-based HMPC formulation for mixed logical dynamical (MLD) systems relevant to problems in behavioral medicine is developed and illustrated on a representative participant model arising from the Just Walk study. The MLD model is developed based on the requirement of granting points for meeting daily step goals and categorical input variables. The algorithm features three degrees-of-freedom tuning for setpoint tracking, measured and unmeasured disturbance rejection that facilitates controller robustness; disturbance anticipation further improves performance for upcoming events such as weekends and weather forecasts. To avoid the corresponding mixed-integer quadratic problem (MIQP) from becoming infeasible, slack variables are introduced in the objective function. Simulation results indicate that the proposed HMPC scheme effectively manages hybrid dynamics, setpoint tracking, disturbance rejection, and the transition between the two phases of the intervention (initiation and maintenance) and is suitable for evaluation in clinical trials.

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