Brief paper: An adaptive optimization scheme with satisfactory transient performance

Authors:
Elias B. Kosmatopoulos
Affiliations:
Dynamic Systems and Simulation Laboratory, Department of Production & Management Engineering, Technical University of Crete, Chania 73100, Greece
Venue:
Automatica (Journal of IFAC)
Year:
2009

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Abstract

Adaptive optimization (AO) schemes based on stochastic approximation principles such as the Random Directions Kiefer-Wolfowitz (RDKW), the Simultaneous Perturbation Stochastic Approximation (SPSA) and the Adaptive Fine-Tuning (AFT) algorithms possess the serious disadvantage of not guaranteeing satisfactory transient behavior due to their requirement for using random or random-like perturbations of the parameter vector. The use of random or random-like perturbations may lead to particularly large values of the objective function, which may result to severe poor performance or stability problems when these methods are applied to closed-loop controller optimization applications. In this paper, we introduce and analyze a new algorithm for alleviating this problem. Mathematical analysis establishes satisfactory transient performance and convergence of the proposed scheme under a general set of assumptions. Application of the proposed scheme to the adaptive optimization of a large-scale, complex control system demonstrates the efficiency of the proposed scheme.