Performance analysis and optimization of supervisory controllers
Efficient manufacturing of products has become more important than ever. Manufacturing systems that produce these products are becoming increasingly complex. They need to be flexible to quickly adapt to changing market demands. Products need to be produced faster, while ensuring their quality. All these constraints make the design of present day manufacturing systems a true challenge. Achieving the economic and quality goals of manufacturing requires the use of a sophisticated controller that directs the scheduling of operations in the system and handles on line changes in the production process. The controller functions as the brains of the system, and controls its behavior. The work of this thesis is motivated by the challenges faced by ASML in designing such controllers for optimal wafer logistics in the various types of lithography machines. These systems manipulate silicon wafers with extreme accuracy at high throughput. The market demands continuous improvement of the accuracy of the imaging, which implies the use of more sophisticated hardware having more resources and actions. This increase leads to a larger solution space in which an optimal controller needs to be found. Designing these optimal controllers is no longer easily feasible by manual effort. Therefore, scalable techniques are needed that can generate an optimal controller from a system model automatically. This thesis introduces a model based method for the design of optimal supervisory controllers. Model based design methods enable design time qualification of controller designs, and allow analysis and optimization of the design before going towards implementation. The method covers the stages of system modeling, controller synthesis, performance optimization, and implementation of a functionally correct and throughput optimal controller. The first contribution of the thesis is a formal modeling approach to compositionally specify both functional and timing aspects of the system. Functional aspects can be considered orthogonally to timing aspects and are specified using two abstraction levels; higher level activities and lower level actions that are executed on system resources. The full system behavior is modeled by activities and their possible orderings. An activity consists of atomic system actions and dependencies among those actions. Activities describe deterministic system operations, that abstract from the different execution orders of internal actions and their timing. The timing semantics of activities is captured using matrices in (max, linear algebra. These matrices express the relationships between the availability times of the system resources, and the release times of the resources after executing the activity. As a result, the controller design can be performed on a much smaller state space compared to an explicit model where timing and actions are present. The supervisory controller makes the