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Título: | Tracking of Unicycle Robots Using Event-Based MPC with Adaptive Prediction Horizon |
Autor: | Sun, Zhongqi; Xia, Yuanqing; Dai, Li; Campoy, Pascual CSIC ORCID | Palabras clave: | Adaptive prediction horizon Event-triggered control Model predictive control (MPC) Self-triggered control Unicycle robots |
Fecha de publicación: | abr-2020 | Editor: | Institute of Electrical and Electronics Engineers | Citación: | IEEE/ASME Transactions on Mechatronics 25 (2): 739-749 (2020) | Resumen: | In this article, we propose two event-based model predictive control (MPC) schemes with adaptive prediction horizon for tracking of unicycle robots with additive disturbances. The schemes are able to reduce the computational burden from two aspects: reducing the frequency of solving the optimization control problem (OCP) to relieve the computational load and decreasing the prediction horizon to decline the computational complexity. Event-triggering and self-triggering mechanisms are developed to activate the OCP solver aperiodically, and a prediction horizon update strategy is presented to decrease the dimension of the OCP in each step. The proposed schemes are tested on a networked platform to show their efficiency. | Versión del editor: | https://doi.org/10.1109/TMECH.2019.2962099 | URI: | http://hdl.handle.net/10261/230225 | DOI: | 10.1109/TMECH.2019.2962099 | ISSN: | 1083-4435 | E-ISSN: | 1941-014X |
Aparece en las colecciones: | (CAR) Artículos |
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