A homotopy-based moving horizon estimation |
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Authors: | Mohammad Abdollahpouri Rien Quirynen Mark Haring Tor Arne Johansen Gergely Takács Moritz Diehl |
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Affiliation: | 1. Faculty of Mechanical Engineering, Institute of Automation, Measurement and Applied Informatics, Slovak University of Technology in Bratislava , Bratislava, Slovakia;2. Department of Microsystems Engineering IMTEK, University of Freiburg, Freiburg, Germany;3. Department of Engineering Cybernetics, Center for Autonomous Marine Operations and Systems (AMOS), Norwegian University of Science and Technology , Trondheim, Norway |
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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. |
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Keywords: | Moving horizon estimation non-convex optimisation nonlinear systems nonlinear state and parameter estimation |
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