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A Distributed Indirect Adaptive Approach to Cooperative Tracking in Networks of Uncertain Single-Input Single-Output Systems

Simone Baldi, Ilario A. Azzollini, Pétros Ioannou

2020IEEE Transactions on Automatic Control33 citationsDOI

Abstract

Current approaches to the cooperative control of network systems are based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge about the (follower) system dynamics: either the dynamics are known, or assumed to be minimum phase, or initial stabilizing controllers are available for each system. The purpose of this article is to show that for single-input single-output systems (SISO) the above assumptions can be relaxed. We propose an indirect adaptive methodology that does not require the knowledge of the parameters of the systems, or the systems to be minimum phase, or initial stabilizing controllers, in order to guarantee asymptotic tracking.

Topics & Concepts

A priori and a posterioriControl theory (sociology)Computer scienceAdaptive controlTracking (education)Control (management)Artificial intelligencePhilosophyPsychologyEpistemologyPedagogyDistributed Control Multi-Agent SystemsAdaptive Control of Nonlinear SystemsNeural Networks Stability and Synchronization
A Distributed Indirect Adaptive Approach to Cooperative Tracking in Networks of Uncertain Single-Input Single-Output Systems | Litcius