Journal article

Extremum seeking of dynamical systems via gradient descent and stochastic approximation methods

SZ Khong, Y Tan, C Manzie, D Nesic

Automatica | Elsevier | Published : 2015


Abstract This paper examines the use of gradient based methods for extremum seeking control of possibly infinite-dimensional dynamic nonlinear systems with general attractors within a periodic sampled-data framework. First, discrete-time gradient descent method is considered and semi-global practical asymptotic stability with respect to an ultimate bound is shown. Next, under the more complicated setting where the sampled measurements of the plant’s output are corrupted by an additive noise, three basic stochastic approximation methods are analysed; namely finite-difference, random directions, and simultaneous perturbation. Semi-global convergence to an optimum with probability one is establ..

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Awarded by Australian Research Council

Funding Acknowledgements

This work was supported by the Swedish Research Council through the LCCC Linnaeus centre and the Australian Research Council (DP120101144). The material in this paper was presented at the 9th Asian Control Conference, June 23-26,2013, Istanbul, Turkey. This paper was recommended for publication in revised form by Associate Editor Raul Ordonez under the direction of Editor Miroslav Krstic.