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Reduced-order Interval-observer Design for Dynamic Systems with Time-invariant Uncertainty

Masoud Pourasghar 1 Vicenç Puig 1 Carlos Ocampo-Martinez 1 Qinghua Zhang 2 
2 I4S - Statistical Inference for Structural Health Monitoring
IFSTTAR/COSYS - Département Composants et Systèmes, Inria Rennes – Bretagne Atlantique
Abstract : This paper addresses the design of reduced-order interval-observers for dynamic systems with time-invariant uncertainty. Because of the limitations of using the set-based approach to preserve the time dependency of parameter uncertainty and the wrapping effect to deal with interval-observers, the trajectory-based interval-observer approach is used with an appropriate observer gain. But, there could be some difficulties to satisfy the conditions for selecting a suitable gain to guarantee the positivity of the resulting observer. Then, a reduced-order observer is designed to reduce the computational complexity and to increase the degree of freedom when selecting the observer gain. Finally, a simulation example is employed for illustrating and analyzing the effectiveness of the proposed approach.
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Submitted on : Tuesday, November 14, 2017 - 5:29:11 PM
Last modification on : Friday, June 17, 2022 - 1:27:50 PM
Long-term archiving on: : Thursday, February 15, 2018 - 3:57:13 PM


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  • HAL Id : hal-01635124, version 1



Masoud Pourasghar, Vicenç Puig, Carlos Ocampo-Martinez, Qinghua Zhang. Reduced-order Interval-observer Design for Dynamic Systems with Time-invariant Uncertainty. IFAC 2017 - 20th World Congress of the International Federation of Automatic Control, Jul 2017, Toulouse, France. pp.1-6. ⟨hal-01635124⟩



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