Proximate model predictive control strategy for autonomous vehicle lateral control

2012 ◽  
Author(s):  
Seung-Hi Lee ◽  
Young Ok Lee ◽  
Bo-Ah Kim ◽  
Chung Choo Chung
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategy ◽  
Autonomous Vehicle ◽  
Lateral Control

Contract-based Hierarchical Model Predictive Control and Planning for Autonomous Vehicle

2020 ◽  
Vol 53 (2) ◽  
pp. 15758-15764
Author(s):  
Mohamed Ibrahim ◽  
Markus Kögel ◽  
Christian Kallies ◽  
Rolf Findeisen
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Hierarchical Model ◽  
Autonomous Vehicle

scholarly journals A Control Method for IPMSM Based on Active Disturbance Rejection Control and Model Predictive Control

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 760
Author(s):  
Fang Liu ◽  
Haotian Li ◽  
Ling Liu ◽  
Runmin Zou ◽  
Kangzhi Liu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Duty Cycle ◽  
Control Strategy ◽  
Disturbance Rejection ◽  
Torque Ripple ◽  
Current Control ◽  
Active Disturbance Rejection Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

In this paper, the speed tracking problem of the interior permanent magnet synchronous motor (IPMSM) of an electric vehicle is studied. A cascade speed control strategy based on active disturbance rejection control (ADRC) and a current control strategy based on improved duty cycle finite control set model predictive control (FCSMPC) are proposed, both of which can reduce torque ripple and current ripple as well as the computational burden. First of all, in the linearization process, some nonlinear terms are added into the control signal for voltage compensation, which can reduce the order of the prediction model. Then, the dq-axis currents are selected by maximum torque per ampere (MTPA). Six virtual vectors are employed to FCSMPC, and a novel way to calculate the duty cycle is adopted. Finally, the simulation results show the validity and superiority of the proposed method.

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