Modelling Control Tasks in Complex Systems

Abstract

The development of control systems for industrial plants have traditionally been based on mathematical models of the causal dynamic interrelationships between plant parameters (e.g., by using knowledge of the physical properties of system components). These models are then used to synthesize control algorithms on the basis of optimization techniques. However, for many important industrial plant control problems, the design problem is not only to cope with the complexity of causal dynamic interactions, but also to cope with the complexity of the end or goal-means structure of the system. Knowledge about plant goal-means structure is important in diagnosis of fault and in planning of compensatory actions (i.e., for strategic plant resource management). Furthermore, it is also important for design of human machine interfaces, as goal-means structures can be used for management, interpretation, and presentation of plant information for the operator. Models of goals-means structures are therefore important for design of integrated supervision and control systems.