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A homotopy-based moving horizon estimation

Abdollahpouri, Mohammad; Quirynen, Rien; Haring, Mark; Johansen, Tor Arne; Takács, Gergely; Diehl, Moritz; Rohal'-Ilkiv, Boris
Journal article, Peer reviewed
Accepted version
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Homotopy_based_MHE_revised1.pdf (638.4Kb)
URI
http://hdl.handle.net/11250/2472271
Date
2017
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  • Institutt for teknisk kybernetikk [2245]
  • Publikasjoner fra CRIStin - NTNU [20889]
Original version
10.1080/00207179.2017.1406150
Abstract
Moving horizon estimation (MHE) solves a constrained dynamic optimisation problem. Including nonlinear dynamics into an optimal estimation problem generally comes at the cost of tackling a non-convex optimisation problem. Here, a particular model formulation is proposed in order to convexify a class of nonlinear MHE problems. It delivers a linear time-varying (LTV) model that is globally equivalent to the nonlinear dynamics in a noise-free environment, hence the optimisation problem becomes convex. On the other hand, in the presence of unknown disturbances, the accuracy of the LTV model degrades and this results in a less accurate solution. For this purpose, some assumptions are imposed and a homotopy-based approach is proposed in order to transform the problem from convex to non-convex, where the sequential implementation of this technique starts with solving the convexified MHE problem. Two simulation studies validate the efficiency and optimality of the proposed approach with unknown disturbances.
Publisher
Taylor & Francis
Journal
International Journal of Control

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