Analysis and Control of Discrete Event Systems

本研究的目标是继续发展离散事件系统（DESs）分析和控制的数学理论。DESs出现在各种实际应用领域，例如，多机器人系统、制造系统、数据库、分布式计算、分布式和分层优化、排队系统、混合变量控制系统、以及复杂过程的高级智能控制。已经提出了许多建议，用于建模和研究感兴趣的DESs的各个方面。最近对逻辑DESs控制的研究有助于我们对DESs分析中涉及的一些基本问题的理解。其他方法，特别是摄动方法和似然比方法对随机DES模型的分析、模拟和优化产生了相当大的影响。该研究的主要目的是通过解决诸如实时约束、算法复杂性、聚合模型、混合变量系统以及使用扰动分析和似然比导数估计的随机优化等问题来扩展这两种方法。为了统一离散事件系统研究中可用的工具，我们还将研究当前模型之间的关系。

The goal of this research is to continue the development of a mathematical theory for the analysis and control of discrete event systems (DESs). DESs arise in a variety of areas of practical application, including, for example, multi-robot systems, manufacturing systems, data bases, distributed computing, distributed and hierarchical optimization, queuing systems, mixed variable control systems, and the higher level intelligent control of complex processes. A number of proposals have been made for modeling and studying the various aspects of DESs of interest. The recent work on the control of logical DESs has contributed to our understanding of some of the fundamental issues involved in the analysis of DESs. Other approaches, particularly perturbation methods and likelihood ratio methods have had considerable impact on the analysis, simulation and optimization of stochastic DES models. The main thrust of the proposed research is to extend these two approaches by addressing issues such as real-time constraints, algorithmic complexity, aggregated models, mixed variable systems, and stochastic optimization using perturbation analysis and likelihood ratio derivative estimates. The relationship between current models will also be investigated with the aim of unifying the tools available for the study of discrete- event systems.