1 research outputs found
Zonotope-based Set-membership Parameter Identification of Linear Systems with Additive and Multiplicative Uncertainties and Its Application to Engine Condition Monitoring
In this paper, we develop two zonotope-based set-membership estimation
algorithms for identification of time-varying parameters in linear models,
where both additive and multiplicative uncertainties are treated explicitly.
The two recursive algorithms can be differentiated by their ways of processing
the data and required computations. The first algorithm, which is referred to
as Cone And Zonotope Intersection (CAZI), requires solving linear programming
problems at each iteration. The second algorithm, referred to as the Polyhedron
And Zonotope Intersection (PAZI), involves linear programming as well as an
optimization subject to linear matrix inequalities (LMIs). Both algorithms are
capable of providing tight overbounds of the feasible solution set (FSS) in our
numerical case studies. Furthermore, PAZI provides an additional opportunity of
further analyzing the relation between the estimation results at different
iterations. An application to health monitoring of marine engines is considered
to demonstrate the utility and effectiveness of the algorithms.Comment: 11 pages, 5 figure