Title :
Plant Friendly Input Design: Convex Relaxation and Quality
Author :
Narasimhan, Sridharakumar ; Rengaswamy, Raghunathan
Author_Institution :
Dept. of Chem. Eng., Clarkson Univ., Potsdam, NY, USA
fDate :
6/1/2011 12:00:00 AM
Abstract :
A common practice in a system identification exercise is to perturb the system of interest and use the resulting data to build a model. The problem of interest in this contribution is to synthesize an input signal that is maximally informative for generating good quality models while being “plant friendly,” i.e., least hostile to plant operation. In this contribution, limits on input move sizes are the plant friendly specifications. The resulting optimization problem is nonlinear and nonconvex. Hence, the original plant friendly input design problem is relaxed which results in a convex optimization problem. We formulate a SemiDefinite Programme using the theory of generalized Tchebysheff inequalities to derive tight bounds on the quality of relaxation. Simulations show that the relaxation results in more plant friendly input signals.
Keywords :
concave programming; nonlinear programming; relaxation theory; SemiDefinite Programme; convex optimization problem; convex relaxation; input signal synthesis; nonconvex; nonlinear; plant friendly input design problem; plant friendly specifications; quality models; system identification; theory of generalized Tchebysheff inequalities; Convex functions; Frequency domain analysis; Linear matrix inequalities; Optimization; Process control; Programming; USA Councils; Convex optimization; Tchebycheff inequalities; input design; semidefinite programming (SDP); system identification;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2011.2132290