Litcius/Paper detail

Gradient free cooperative seeking of a moving source

Michael Elad, Chris Manzie, Tony A. Wood, Daniel Zelazo, Iman Shames

2023Automatica12 citationsDOIOpen Access PDF

Abstract

In this paper, we consider the optimisation of a time varying scalar field by a network of agents with no gradient information. We propose a composite control law, blending extremum seeking with formation control in order to converge to the extrema faster by minimising the gradient estimation error. By formalising the relationship between the formation and the gradient estimation error, we provide a novel analysis to prove the convergence of the network to a bounded neighbourhood of the field’s time varying extrema. We assume the time-varying field satisfies the Polyak–Łojasiewicz inequality and the gradient is Lipschitz continuous at each iteration. Numerical studies and comparisons are provided to support the theoretical results.

Topics & Concepts

Maxima and minimaLipschitz continuityBounded functionMathematicsApplied mathematicsScalar fieldMathematical optimizationConvergence (economics)Field (mathematics)Gradient methodGradient descentNeighbourhood (mathematics)Control theory (sociology)Computer scienceControl (management)Mathematical analysisArtificial neural networkPure mathematicsEconomicsArtificial intelligenceMathematical physicsEconomic growthMachine learningExtremum Seeking Control SystemsMathematical Biology Tumor Growththermodynamics and calorimetric analyses