A decision-based approach to the integration of chemical process design and control structure synthesis.

摘要

The control of a chemical plant is concerned with analysis, design, and implementation of control systems that facilitate the achievement of process safety, production rates, and product quality. Traditionally, controller synthesis focused on each unit operation rather than the entire plant. Thus, the resulting control strategies may be very far from optimal because the interactions and inter-dependencies among the units and the variables are not considered. Other obstacles that deter a plantwide controller synthesis focus include the large dimensionality of the problem, the multivariable nature of the controller design, input and output constraints, equipment constraints, and the high degree of non-linearities associated with the transport, diffusion, and kinetic processes. A multitude of different approaches have been suggested for plantwide control structure synthesis. A large number of these approaches rely on experiential knowledge applied in a systematic manner, but the order in which the objectives are addressed is not consistent from one approach to the next. In this work, a novel and systematic approach to the design of plantwide controllers is presented with the objective of prioritizing among complementary and competing design, operational and control objectives. Once the priority is found, the controller design can be carried out with any number of existing control theories.;The methodology begins with addressing the dimensionality of the plantwide control problem by applying a decision-based approach, the modified analytic hierarchical process, to decompose the process flowsheet into modules that address specific design and operational objectives. Once the modules are identified, they are analyzed using system-theoretic tools. Next, the control and manipulated variables are selected, the control structure can be developed and validated. The next step is to combine all the modules and their control structures and verify that together the performance of the plant and the control structure is stable and satisfactory. Several examples, simple to complex, are provided to demonstrate the efficacy of the approach.