Journal of System Simulation
Abstract
Abstract: Aiming at the low control accuracy and poor robustness of traditional trajectory tracking controller based on the tracking error model in complex driving environment, a robust model predictive trajectory tracking control strategy is designed. The vehicle convex multicellular dynamic model is used to explicitly describe the vehicle dynamic characteristics, and the robust performance objective function is designed in combination with the trajectory tracking multi-objective constraint, and the state feedback control law is solved through the linear matrix inequality optimization. Feedforward control is introduced to eliminate the steady-state errors and improve the tracking accuracy. The simulation result shows that under the different driving conditions on the basis of ensuring the vehicle tracking accuracy, the controller can effectively improve the transmission stability and the robustness is stronger.
Recommended Citation
Lu, Hongguang and Zhao, Shuen
(2022)
"Research on Intelligent Vehicle Trajectory Tracking Control Based on Robust Model Prediction,"
Journal of System Simulation: Vol. 34:
Iss.
1, Article 17.
DOI: 10.16182/j.issn1004731x.joss.20-0686
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss1/17
First Page
153
Revised Date
2020-11-17
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-0686
Last Page
162
CLC
TP391;U461.99
Recommended Citation
Lu Hongguang, Zhao Shuen. Research on Intelligent Vehicle Trajectory Tracking Control Based on Robust Model Prediction[J]. Journal of System Simulation, 2022, 34(1): 153-162.
DOI
10.16182/j.issn1004731x.joss.20-0686
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons