Time-delay Induced Stochastic Optimization and Extremum Seeking

European Control Conference (ECC), pp. 1636–1641

Abstract

In this paper a novel stochastic optimization and extremum seeking algorithm is presented, one which is based on time-delayed random perturbations and step size adaptation. For the case of a one-dimensional quadratic unconstrained optimization problem, global exponential convergence in expectation and global exponential practical convergence of the variance of the trajectories are proven. The theoretical results are complemented by numerical simulations for one-and multidimensional quadratic and non-quadratic objective functions.

Authors 4

1. Naum Dimitrieski Aachen Chair of Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Intelligent Control Systems,Aachen,Germany,52062

2. Michael Reyer Aachen Chair of Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Intelligent Control Systems,Aachen,Germany,52062

3. Mohamed-Ali Belabbas

   University of Illinois Urbana-Champaign

   Affiliation as printed

   University of Illinois at Urbana-Champaign,Coordinated Science Laboratory,Urbana,IL,USA,61801

4. Christian Ebenbauer Aachen Chair of Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Intelligent Control Systems,Aachen,Germany,52062