Abstract
This paper addresses the problem of estimating the state for a class of uncertain discrete-time linear systems with constraints by using an optimization-based approach. The proposed scheme uses the moving horizon estimation philosophy together with the game theoretical approach to the H∞ filtering to obtain a robust filter with constraint handling. The used approach is constructive since the proposed moving horizon estimator (MHE) results from an approximation of a type of full information estimator for uncertain discrete-time linear systems, named in short H∞-MHE and H∞-full information estimator, respectively. Sufficient conditions for the stability of the H∞-MHE are discussed for a class of uncertain discrete-time linear systems with constraints. Finally, since the H∞-MHE needs the solution of a complex minimax optimization problem at each sampling time, we propose an approximation to relax the optimization problem and hence to obtain a feasible numerical solution of the proposed filter. Simulation results show the effectiveness of the robust filter proposed.
Original language | English |
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Pages (from-to) | 326–341 |
Number of pages | 16 |
Journal | International Journal of Robust and Nonlinear Control |
Volume | 28 |
Issue number | 1 |
DOIs | |
Publication status | Published - 10 Jan 2018 |
Keywords
- Constrained estimation
- Moving horizon estimation
- Optimization
- Robust estimation
- Uncertain linear systems
- constrained estimation
- optimization
- robust estimation
- moving horizon estimation
- uncertain linear systems