In this paper, we study the control problems of distributed parameter systems, and discuss the limitations of traditional control methods. In recent years, social factors have gradually become an essential parameter of system modeling. For complex distributed parameter systems, the accurate modeling becomes difficult. With the rapid development of the network and the technology of big data and cloud computing, based on the advanced control theory of large-scale computing, we introduce the idea of parallel control to the control of distributed parameter systems. Parallel control is a method to accomplish tasks through the interaction of virtual and actual. Its core is to model the complex distributed parameter system on artificial society or artificial system, then analyze and evaluate it by computational experiment, and finally control and manage the distributed parameter system by parallel execution. Data-driven control and computational control are used in this method, which is a control idea that adapts to the rapid development of society.

中文翻译：

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分布式参数系统的并行控制


在本文中，我们研究了分布参数系统的控制问题，并讨论了传统控制方法的局限性。近年来，社会因素逐渐成为系统建模的重要参数。对于复杂的分布参数系统，精确建模变得困难。随着网络、大数据、云计算技术的快速发展，基于大规模计算的先进控制理论，将并行控制的思想引入到分布式参数系统的控制中。并行控制是一种通过虚拟与实际交互来完成任务的方法。其核心是在人工社会或人工系统上对复杂的分布参数系统进行建模，然后通过计算实验进行分析和评估，最后通过并行执行来控制和管理分布参数系统。该方法采用了数据驱动控制和计算控制，是适应社会快速发展的控制思想。