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IMA Journal of Mathematical Control and Information 1989 6(1):39-61; doi:10.1093/imamci/6.1.39
© 1989 by Institute of Mathematics and its Applications
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A New Two-Model Approach for Optimizing Control of Large-Scale Steady-State Systems

J. LIN, C. KAMBHAMPATI and P. D. ROBERTS

Institute of Systems Engineering, Xi'an Jiaotong University, Xi'an Peoples Republic of China
Control Engineering Centre, City University Northampton Square London EC1V 0HB, U.K.

A novel two-model approach for hierarchical system optimization and parameter estimation of large-scale industrial processes is described which is considerably more efficient and reliable than previous hierarchical methods for integrated system optimization and parameter estimation (ISOPE), in the sense that it takes far fewer changes of controller set points to produce the real optimum, and its convergent conditions are weaker.

Other advantages of this new approach are that the number of controller set-point changes does not depend on the number of inequality constraints that are tight at the optimum, and it is possible to provide sufficient conditions for global convergence which are nearly the same as those of the centralized ISOPE method.

Optimality of the algorithm is examined, and a proof of the global convergence of the algorithm is presented. Computer simulations are used to demonstrate the behaviour of the algorithm.


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