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Tracking of Unicycle Robots Using Event-Based MPC with Adaptive Prediction Horizon

AuthorsSun, Zhongqi; Xia, Yuanqing; Dai, Li; Campoy, Pascual CSIC ORCID
KeywordsAdaptive prediction horizon
Event-triggered control
Model predictive control (MPC)
Self-triggered control
Unicycle robots
Issue DateApr-2020
PublisherInstitute of Electrical and Electronics Engineers
CitationIEEE/ASME Transactions on Mechatronics 25 (2): 739-749 (2020)
AbstractIn 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.
Publisher version (URL)https://doi.org/10.1109/TMECH.2019.2962099
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