Continuous and discrete state estimation for switched LPV systems using parameter identification

Abstract

In this paper the problem of discrete and continuous state estimation for a class of uncertain switched LPV systems is addressed. Parameter identification techniques are applied to realize an approximate identification of the scheduled parameters of a switched LPV system with certain uncertainties and/or disturbances. A discrete state estimation is achieved using the parameter identification. A Luenberger-like hybrid observer, based on discrete state information and LMIs approach, is used for the continuous state estimation. The simplicity of the proposed method is one of the main advantages of this paper. The feasibility of the proposed method is illustrated by simulations.

Actuator multiplicative fault estimation in discrete-time LPV systems using switched observers

“…that, taking into account Ξ l i = P l L l i , and (52), (54) and (55), becomes (31). If the same process is applied to (57) using the coefficients α i (θ(k)) and χ l j (u(k)) and taking into account (55)-(57), (32) would be obtained.…”

“…However, only a few works have dealt with the problem of observer design for switched LPV system, e.g. [31], where a Luenberger-like hybrid LPV observer was used for the continuous state estimation, and [32], where an adaptive switched LPV observer was proposed for the joint state and parameter estimation.…”

Dynamic event‐based dissipative asynchronous control for singular Markov jump LPV systems with general transition rates

“…Remark 10. (1) Compared with the reference [23], the optimisation of PDLMIs in Theorem 2 is more complex. Firstly, the PDLMIs in Theorem 2 are determined by the SMJLPV system and the designed asynchronous controller.…”

On Interval Observer Design for Continuous-Time LPV Switched Systems

“…The main advantage of this strategy is that it allows one to apply several developed frameworks for linear systems. In the literature, many researches have been carried out about LPV systems [1,10,24]. However in practice, systems are often subject to exogenous uncertainties (state a Conservatoire National des Arts et Métiers (CNAM), Cedric -Lab, HESAM Université, 292 Rue Saint-Martin, 75141 Paris Cedex 03, France, E-mail: chaima.zammali@etu.upmc.fr, E-mail: jeremy.vangorp@lecnam.net, E-mail: tarek.raissi@cnam.fr disturbance, measurement noise) and endogenous ones (parametric uncertainties).…”