Hierarchical Adaptive Techniques for Optimizing Control of Large-Scale Steady-State Systems: Optimality, Iterative Strategies,and their Convergence

A hierarchical structure for on-line steady-state optimizingcontrol of interconnected systems is discussed which utilizesthe available mathematical model more efficiently than in previoustechniques, in spite of large model-reality differences. Thestructure is of an iterative type and uses both the mathematicalmodel of the system and the system output measurements. Thestructure produces a control which satisfies necessary optimalityconditions, provided that the system mathematical model is point-parametric.Several iterative strategies for finding a solution are presented.The strategies are compared with respect to their applicability,the total number of set-point changes needed to find solution,and the amount of information exchanged between control unitsand process during iterations.