Supervisory Control and Regulation of Discrete Dynamical Systems

我们建议的研究是在工程和应用数学的分支，称为自动控制或 有时是控制论，即反馈系统的科学和技术。这样的系统旨在维护一些关键的 变量(S)在可接受的范围内。例如，飞机的自动飞行员会纠正原本可能存在的风扰扰 驾驶飞机偏离航线，也许是灾难性的。我们特别感兴趣的是系统，例如交通系统，它们必须响应瞬时 事件，如到达车辆的十字路口；以及制造系统，必须对新的部件订单或机器故障做出反应。 另一个例子是汽车中的按钮系统，尽管它是由驾车者“随机”启动的，但其设计应该是永远不会掉进 逻辑错误，如“挂起”或阻塞。 这样的离散事件系统及其控制需要控制理论和计算机科学相结合的新的和专门的技术。一项重大挑战 这些系统可能(在逻辑上)非常庞大和复杂。例如，汽车按钮系统可能潜在地进入数百万不同的内部 状态或逻辑配置。这可能会导致对控制工程设计所需的计算能力的几乎压倒性的要求。 我们正在开发正式的(即系统的和数学上严格的)方法，根据有效的架构原则组织这些系统。 这样的系统体系结构可以是分层的，即，类似于管理级别，将组件组组织成逻辑“层” 在企业或政府组织中。在那里，每个级别接受上一级的命令，并向下一级发出控制命令，但 反馈链接，通过该链接，给定级别可以向更高级别报告有价值的绩效数据。或者，可以组织主要系统组件 分布到通过网络相互通信的半自主智能代理。事实上，这种垂直和组合的许多变体和组合 在实践中采用了水平架构。任何系统架构的目标都是使复杂的系统既透明(即人性化 可理解性)和可计算性(即，能够控制保证系统将按照规范运行的设计)。我们的终极目标 就是制定建筑规律，以指导选择最适合给定控制任务的架构。 一个平行的研究目标是控制理论的内模原理(IMP)的扩展，根据该原理，一个“好的”控制器(在某种技术意义上) 必须配备关于其环境动态结构的特定情报。特别令人感兴趣的将是IMP在 上述离散事件系统的控制体系结构。

Our proposed research lies in the branch of engineering and applied mathematics called automatic control or sometimes cybernetics, namely the science and technology of feedback systems. Such systems are designed to maintain some critical variable(s) within an acceptable range. For instance, an aircraft's automatic pilot corrects for wind disturbances which might otherwise drive the plane off course, perhaps disastrously. Of specific interest to us are systems, such as traffic systems, which must respond to instantaneous events, like the arrival at an intersection of a vehicle; and manufacturing systems, which must respond to a new part order or a machine breakdown. Another example is the pushbutton system in an automobile which, though "randomly" activated by the motorist, should be designed never to fall into a logical error like "hangup" or blocking. Such discrete-event systems and their control call for new and specialized techniques at the interface of control theory and computer science. A major challenge is that these systems can be (logically) very large and complex. For instance, the automobile pushbutton system may potentially enter many millions of different internal states or logical configurations. This may lead to almost overwhelming requirements on the computing power needed for control engineering design. We are developing formal (i.e. systematic and mathematically rigorous) methods of organizing such systems according to effective architectural principles. Such a system architecture could be hierarchical, namely an organization of component groups into logical "layers", analogous to the levels of management in a business or governmental organization. There each level takes orders from the one above, and issues control commands to the one below, but with feedback links by which a given level can report valuable performance data to the level above. Alternatively one might organize the main system components distributively into semi-autonomous smart agents that intercommunicate by networking. In fact many variations and combinations of such vertical and horizontal architectures are employed in practice. The objective of any system architecture is to render a complex system both transparent (i.e. humanly intelligible) and computable (i.e. amenable to control design which guarantees that the system will behave in accordance with specification). Our ultimate goal is to develop laws of architecture to guide the choice of architecture best suited to a given control task. A parallel research goal is extension of the internal model principle (IMP) of control theory, according to which a "good" controller (in a certain technical sense) must be equipped with specific intelligence concerning the dynamical structure of its environment. Of especial interest will be the incorporation of the IMP in the control architectures of discrete-event systems as outlined above.