Dual Particle Output Feedback Control based on Lyapunov drifts for nonlinear systems

Abstract : This paper presents a dual receding horizon output feedback controller for a general non linear stochastic system with imperfect information. The novelty of this controller is that stabilization is treated, inside the optimization problem, as a negative drift constraint on the control that is taken from the theory of stability of Markov chains. The dual effect is then created by maximizing information over the stabilizing controls which makes the global algorithm easier to tune than our previous algorithm. We use a particle filter for state estimation to handle nonlinearities and multimodality. The performance of this method is demonstrated on the challenging problem of terrain aided navigation.
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Communication dans un congrès
2018 IEEE Conference on Decision and Control (CDC), Dec 2018, Miami Beach, United States. pp.250-255, 2018 IEEE Conference on Decision and Control (CDC). 〈10.1109/CDC.2018.8619640〉
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Dernière modification le : mercredi 13 février 2019 - 09:54:33
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Emilien Flayac, Karim Dahia, Bruno Hérissé, Frédéric Jean. Dual Particle Output Feedback Control based on Lyapunov drifts for nonlinear systems. 2018 IEEE Conference on Decision and Control (CDC), Dec 2018, Miami Beach, United States. pp.250-255, 2018 IEEE Conference on Decision and Control (CDC). 〈10.1109/CDC.2018.8619640〉. 〈hal-01744262〉

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