Extremum seeking under stochastic noise and applications to mobile sensors

Authors:
Miloš S. Stanković;Dušan M. Stipanović
Affiliations:
ACCESS Linnaeus Center, School of Electrical Engineering, Royal Institute of Technology, 100 44 Stockholm, Sweden;Department of Industrial and Enterprise Systems Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, IL, USA
Venue:
Automatica (Journal of IFAC)
Year:
2010

Citing 3
Cited 3

Stochastic systems: estimation, identification and adaptive control

Stochastic systems: estimation, identification and adaptive control
Brief paper: Extremum seeking for moderately unstable systems and for autonomous vehicle target tracking without position measurements

Automatica (Journal of IFAC)
Brief Stability of extremum seeking feedback for general nonlinear dynamic systems

Automatica (Journal of IFAC)

Multivariable Newton-based extremum seeking

Automatica (Journal of IFAC)
Lie bracket approximation of extremum seeking systems

Automatica (Journal of IFAC)
Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

Automatica (Journal of IFAC)

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Abstract

In this paper the extremum seeking algorithm with sinusoidal perturbations has been extended and modified in two ways: (a) the output of the system is corrupted with measurement noise; (b) the amplitudes of the perturbation signals, as well as the gain of the integrator block, are time varying and tend to zero at a pre-specified rate. Convergence to the extremal point, with probability one, has been proved. Also, as a consequence of being able to cope with a stochastic environment, it has been shown how the proposed algorithm can be applied to mobile sensors as a tool for achieving the optimal observation positions. The proposed algorithm has been illustrated through several simulations.