Supervisory Control and Regulation of Discrete Dynamical Systems

我们提出的研究属于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。 这些系统的设计是为了保持一些关键的 变量在可接受范围内。 例如，飞机的自动驾驶仪可以修正风的干扰，否则， 让飞机偏离航线，也许会造成灾难 我们特别感兴趣的是系统，如交通系统，它必须响应瞬时的 事件，如到达车辆的交叉路口;和制造系统，必须响应新的零件订单或机器故障。 另一个例子是汽车中的自动驾驶系统，尽管它是由驾驶者“随机”启动的，但应该设计成永远不会落入 逻辑错误，如“hangup”或阻塞。 这种离散事件系统及其控制要求在控制理论和计算机科学的接口新的和专门的技术。 一项重大挑战 这些系统可以（逻辑上）非常庞大和复杂。 例如，汽车电子系统可能潜在地进入数百万个不同的内部 状态或逻辑配置。 这可能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样的系统。 这样的系统架构可以是分层的，即将组件组组织成逻辑“层”，类似于管理级别 在商业或政府组织中。在那里，每一级都接受上级的命令，并向下级发出控制命令，但 反馈链接，通过该链接，给定级别可以向上一级别报告有价值的性能数据。或者，可以组织主要系统组件 分布式地分成通过网络相互通信的半自治智能代理。 事实上，这种垂直和垂直方向的许多变化和组合都是可能的。 在实践中采用水平结构。 任何系统架构的目标都是使复杂系统既透明（即人性化 可理解的）和可计算的（即服从控制设计，保证系统将按照规范运行）。 我们的最终目标 是发展法律的架构，以指导架构的选择最适合于一个给定的控制任务。 一个平行的研究目标是扩展控制理论的内模原理（IMP），根据该原理，一个“好”的控制器（在一定的技术意义上） 必须配备有关其环境的动态结构的特定智能。 特别令人感兴趣的是将IMP纳入 如上所述的离散事件系统的控制架构。

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.