Journal
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
Volume 31, Issue 10, Pages 4744-4763Publisher
WILEY
DOI: 10.1002/rnc.5535
Keywords
adaptive control; lateral path following; model predictive control; unmanned ground vehicle
Funding
- Fundamental Research Funds for the Central Universities
- National Natural Science Foundation of China [61922063, U1764261, 61773289]
- Natural Science Foundation of Shanghai [19ZR1461400]
- Shanghai International Science and Technology Cooperation Project [18510711100]
- Shanghai Shuguang Project [18SG18]
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This article presents a dual-mode model predictive control algorithm based on an adaptive event triggered mechanism for the lateral path following problem of unmanned ground vehicles with bounded disturbances. The proposed algorithm ensures tracking accuracy and reduces optimization computation compared to existing MPC algorithms. Feasibility and stability are guaranteed through constraint region parameter design. Simulation results of the vehicle dynamics model are provided and comparisons are made.
In this article, the lateral path following problem of unmanned ground vehicle with bounded disturbances is studied. A dual-mode model predictive control (MPC) algorithm based on adaptive event triggered mechanism is proposed. Compared with the existing MPC algorithm, adaptive event triggered model predictive control (AEMPC) can ensure the tracking accuracy and reduce the optimization computation. Feasibility and stability of AEMPC algorithm are guaranteed by constraint region parameter design. Finally, simulation results of the vehicle dynamics model are given, and the comparisons are made.
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