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1 – 1 of 1Qun Cao, Yuanqing Xia, Zhongqi Sun and Li Dai
This paper aims to design an algorithm which is used to deal with non-linear discrete systems with constraints under the lower computation burden. As a result, we solve the…
Abstract
Purpose
This paper aims to design an algorithm which is used to deal with non-linear discrete systems with constraints under the lower computation burden. As a result, we solve the non-holonomic vehicle tracking problem with the lower computational load and the convergence performance.
Design/methodology/approach
A fusion event-triggered model predictive control version is developed in this paper. The authors designed a shrinking prediction strategy.
Findings
The fusion event-triggered model predictive control scheme combines the strong points of event triggered and self-triggered methods. As the practical state approaches the terminal set, the computational complexity of optimal control problem (OCP) decreases.
Originality/value
The proposed strategy has proven to stabilize the system and also guarantee a reproducible solution for the OCP. Also, it is proved to be effected by the performance of the simulation results.
Details