The interplay between identi cation of a predictor and the convexity of an associated optimization-based control problem is studied. The reason for the appearance of nonconvexity is investigated and a method to favour convexity of the optimization-based control problem in the identi cation problem is suggested. Further, a parametrization which makes the identi cation problem tractable is propos...

∗ Associate Fellow AIAA; President, Innovative Technology Applications Company, Chesterfield, MO † Post Doctoral Researcher, presently residing in Argentina ‡ Ph. D. Candidate, Dept. of Mathematics § Director of the Center for Research in Scientific Computation and University Professor and Drexel Professor of Mathematics ¶ Associate Professor of Mathematics and Associate Director of the Center ...

Plantwide control is concerned with the structural decisions involved in the control system design of a chemical plant (C.S. Foss, Critique of chemical process control theory, AIChE Journal 19(2), 1973) 209±214; ``Which variables should be controlled, which variables should be measured, which inputs should be manipulated, and which links should be made between them?'' In particular, the ®rst is...

The following important question is frequently overlooked: Which variables should we control? The answer is related to finding a simple and robust way of implementing the optimal operating strategy. It is argued that the controlled variables should be those that that give “self-optimizing control”, which is when acceptable operation is achieved with constant setpoints for the controlled variabl...

This paper presents a novel method for designing robust MPC schemes that are self-optimizing in terms of disturbance attenuation. The method employs convex control Lyapunov functions and disturbance bounds to optimize robustness of the closed-loop system on-line, at each sampling instant a unique feature in MPC. Moreover, the proposed MPC algorithm is computationally efficient for nonlinear sys...

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This paper reviews the role of self-optimizing control (SOC) and necessary conditions of optimality tracking (NCO tracking). We argue that self-optimizing control is not an alternative to real-time optimization (RTO), NCO tracking or model predictive control (MPC), but is to be seen as complementary. In self-optimizing control we determine controlled variables (CV), that keep the process close ...