Interval Estimation for Discrete-Time Linear Parameter-Varying System with Unknown Inputs

• Published in: Proceedings of the IEEE Conference on Decision & Control pp. 4002 - 4007
• Main Authors: Chevet, Thomas, Dinh, Thach Ngoc, Marzat, Julien, Raissi, Tarek
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.12.2021
• Subjects: Conferences; Discrete-time systems; Estimation; Interval observer; Linear matrix inequalities; Linear parameter-varying system; Noise measurement; Numerical simulation; Observers; Perturbation methods; Unknown input observer
• ISSN: 2576-2370
• DOI: 10.1109/CDC45484.2021.9683335

This paper proposes a new interval observer for joint estimation of the state and unknown inputs of a discrete-time linear parameter-varying (LPV) system with an unmeasurable parameter vector. This system is assumed to be subject to unknown inputs and unknown but bounded disturbances and measurement noise, while the parameter- varying matrices are elementwise bounded. Considering the unknown inputs as auxiliary states, the dynamics are rewritten as discrete-time LPV descriptor dynamics. A new structure of interval observer is then used, providing more degrees of freedom than the classical change of coordinates-based structure. The observer gains are computed by solving linear matrix inequalities derived from cooperativity condition and L ∞ norm. Numerical simulations are run to show the efficiency of the proposed observer.