Parallel Control: A Method for Data-Driven and Computational Control
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摘要: 本文简述平行控制的理念、概念及基本方法与应用, 主要强调虚实互动的平行扩展方式与同时计算的并行划分方式的不同之处. 平行控制方法是ACP理论在控制领域中的具体应用, 其核心是利用人工系统进行建模和表示、通过计算实验进行分析和评估、最后借助平行执行实现对复杂系统的控制和管理. 这一控制方法是反馈控制, 特别是自适应控制方法向复杂系统问题扩展的自然结果, 是一种迈向数据驱动控制和计算控制的必然且有效途径.Abstract: This paper introduces the concept, architecture, process and application of a new data-driven and computational control approach, called parallel control. The emphasis here is to illustrate the difference between the proposed system expansion scheme for parallel control through cyber-physical-social interaction and the traditional divide-and-conquer method for parallel computing through concurrent task execution. The theory of parallel control comes directly from the ACP approach, where artificial systems are used for modeling and representation, computational experiments are utilized for analysis and evaluation, and parallel execution are conducted for control and management of complex systems. Parallel control can be considered as the extension of feedback control, especially adaptive control, for dealing with problems involved with both engineering and social complexities. Case studies of this new control approach in transportation, production, and social management are presented and discussed.
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Key words:
- Parallel control /
- complex systems /
- ACP approach /
- adaptive control /
- computational control /
- data-driven
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