Compact Representations for Adaptive Critic Designs

自适应批评设计的紧凑表示

• 批准号: 0201076
• 负责人: Sivasubramanya Balakrishnan
• 金额: $ 8.98万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0201076&HistoricalAwards=false
• 关键词: Compact; Representations; Adaptive; Critic; Designs

ABSTRACTCompact Value Functions for Value-Based Control of Distributed SystemsThis project will extend the P1's work on a previous NSF grant on intelligent control for distributed systems. That previous grant started from recent results in value-based intelligent control, sometimes called approximate dynamic programming (ADP) or reinforcement learning (RL). Older forms of control typically guarantee stability, under certain theoretical assumptions, but do not focus on optimal performance. The new methods focus on optimal performance, without assuming linearity or perfect knowledge of system dynamics.By using new model-based versions of ADP or RI, and by developing value approximation schemes suitable for distributed systems, he was able to demonstrate new levels of performance in test problems in distributed tasks such as fluid flow control and missile interception. The new project is intended to be the first stage in addressing larger and more general distributed control problems, such as manufacturing processes, job scheduling, network traffic, etc. The first stage will be to explore more powerful value approximation schemes, in order to enhance the ability to control systems governed by partial differential equations, such as fluid flows encountered in aerospace, plasma and industrial applications, to the extent possible in a small-scale exploratory effort.

分布式系统基于值的控制的紧凑值函数这个项目将扩展P1的工作在以前的NSF授予分布式系统的智能控制。之前的资助始于基于值的智能控制的最新成果，有时称为近似动态规划（ADP）或强化学习（RL）。旧的控制形式通常在某些理论假设下保证稳定性，但不关注最佳性能。新方法专注于最佳性能，无需假设线性或系统动力学的完美知识。通过使用新的基于模型的ADP或RI版本，并通过开发适用于分布式系统的值近似方案，他能够在流体流量控制和导弹拦截等分布式任务的测试问题中展示新的性能水平。该新项目旨在成为解决更大和更一般的分布式控制问题的第一阶段，例如制造过程，作业调度，网络流量等。第一阶段将探索更强大的数值逼近方案，以提高控制由偏微分方程控制的系统的能力，例如航空航天，等离子体和工业应用中遇到的流体流动，尽可能地进行小规模的探索。