Abstract
The chapter introduces a technique for multi-variable extremum seeking and gradient seeking, employing distinct noise sources for each of the distinct inputs being tuned. Convergence is proved using the averaging method, with an estimate of the convergence rate being related to the eigenvalues of the Hessian matrix of the map.
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© 2012 Springer-Verlag London
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Liu, SJ., Krstic, M. (2012). Multi-parameter Stochastic Extremum Seeking and Slope Seeking. In: Stochastic Averaging and Stochastic Extremum Seeking. Communications and Control Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-4087-0_8
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DOI: https://doi.org/10.1007/978-1-4471-4087-0_8
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4086-3
Online ISBN: 978-1-4471-4087-0
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