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.
Original language | English (US) |
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Pages (from-to) | 1243-1251 |
Number of pages | 9 |
Journal | Automatica |
Volume | 46 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2010 |
Keywords
- Convergence
- Extremum seeking
- Mobile sensors
- Noise source localization
- Stochastic recursive algorithms
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering