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• W180784818 abstract "Nearly every model predictive control (MPC) algorithm is premised on knowledge of the system’s state. As a result, state estimation is vital to good MPC performance. Moving horizon estimation (MHE) is an optimization-based state estimation algorithm. Similar to MPC, it relies on the minimization of a sum of stage costs subject to a dynamic model. Unlike MPC, however, conditions under which MHE is robustly stable have been slow to emerge. Recently, several results have appeared about the robust stability of MHE. We generalize the result on the robust stability of MHE without a max-term presented in Müller (Automatica 79:306–314, 2017). using assumptions inspired by the result in Hu (Robust stability of optimization-based state estimation under bounded disturbances. ArXiv e-prints, 2017). Furthermore, we show that all systems that are covered by the assumptions used in those previous works satisfy a certain form of exponential incremental input/output-to-state stability." @default.
• W180784818 created "2016-06-24" @default.
• W180784818 creator A5026908362 @default.
• W180784818 creator A5033056557 @default.
• W180784818 date "2018-09-01" @default.
• W180784818 modified "2023-10-16" @default.
• W180784818 title "Moving Horizon Estimation" @default.
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• W180784818 doi "https://doi.org/10.1007/978-3-319-77489-3_5" @default.
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