SYRODec 10, 2021

An Adaptive Observer for Uncertain Linear Time-Varying Systems with Unknown Additive Perturbations

arXiv:2112.05497v139 citations
Originality Incremental advance
AI Analysis

This work addresses state estimation challenges in control systems with uncertainties, but it appears incremental as it builds on existing observer designs for uncertain systems.

The paper tackled the problem of adaptive state observation for linear time-varying systems with unknown parameters and additive perturbations, proposing a globally convergent state observer that requires only a weak excitation assumption.

In this paper we are interested in the problem of adaptive state observation of linear time-varying (LTV) systems where the system and the input matrices depend on unknown time-varying parameters. It is assumed that these parameters satisfy some known LTV dynamics, but with unknown initial conditions. Moreover, the state equation is perturbed by an additive signal generated from an exosystem with uncertain constant parameters. Our main contribution is to propose a globally convergent state observer that requires only a weak excitation assumption on the system.

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