Model Predictive Control of a Low Speed Munition

Author(s):  
Nathan Slegers
Author(s):  
Yihuai Zhang ◽  
Baijun Shi ◽  
Xizhi Hu ◽  
Wandong Ai

Abstract Automated valet parking is a part of autonomous vehicles. Path tracking is a vital capability of autonomous vehicles. In the scenario of automatic valet parking, the existing control algorithm will produce a high tracking error and a high computational burden. This paper proposes a path-tracking algorithm based on model predictive control to adapt to low-speed driving. By using the model predictive control method and vehicle kinematics model, a path tracking controller is designed. Combining the dual algorithm to further optimize the solver, a new QPKWIK solver is proposed. The simulation results show that the solution time of the QPKWIK solver is 25% less than that of the QP solver, and the tracking error is reduced by up to 41% compared with the QP solver. In the parking lot, the tracking performance is tested under four common scenarios, and the experimental results show that this controller has better tracking performance.


2018 ◽  
Vol 39 (3) ◽  
pp. 167-177 ◽  
Author(s):  
Niels Henrik Pedersen ◽  
Per Johansen ◽  
Anders Hedegaard Hansen ◽  
Torben Ole Andersen

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