The article discusses a novel approach for state reconstruction in uncertain linear systems with overparameterization and unknown additive perturbations. The proposed adaptive observer aims to reconstruct the physical state of the original system, ensuring exponential convergence of the reconstruction error to zero under certain conditions. By using a parametrization method for uncertain linear systems with unknown additive perturbations, along with dynamic regressor extension and mixing procedures, the authors provide detailed stability analysis and simulation results to validate their theoretical findings. The study extends previous work by addressing systems with disturbances generated by exosystems with fully uncertain parameters.
The introduction highlights the importance of simultaneous reconstruction of unmeasured system states and unknown parameters using adaptive observers. Two main design principles are discussed based on existing studies by R. Carroll and K. S. Narendra.
The article presents techniques based on system transformation to an observer canonical form for parameter estimation in linear time-invariant systems. It also introduces a novel adaptive algebraic observer for uncertain linear time-varying systems with unknown additive perturbations.
Overall, the study focuses on developing an adaptive observer that can accurately reconstruct physical states in uncertain linear systems, providing a significant advancement in state estimation methodologies.
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by Anton Glushc... a las arxiv.org 03-14-2024
https://arxiv.org/pdf/2308.10289.pdfConsultas más profundas