数学
模型预测控制
最优控制
公制(单位)
理想(伦理)
状态空间
控制理论(社会学)
扩展(谓词逻辑)
数学优化
应用数学
控制(管理)
计算机科学
统计
运营管理
哲学
人工智能
经济
认识论
程序设计语言
作者
Georgi Angelov,Alberto Domínguez Corella,Vladimir M. Veliov
摘要
The paper investigates the accuracy of the model predictive control (MPC) method for finding on-line approximate optimal feedback control for Bolza-type problems on a fixed finite horizon. The predictions for the dynamics, the state measurements, and the solution of the auxiliary open-loop control problems that appear at every step of the MPC method may be inaccurate. The main result provides an error estimate of the MPC-generated solution compared with the optimal open-loop solution of the "ideal" problem, where all predictions and measurements are exact. The technique of proving the estimate involves an extension of the notion of strong metric subregularity of set-valued maps and utilization of a specific new metric in the control space, which makes the proof nonstandard. The result is specialized for two problem classes: coercive problems and affine problems.
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