.png){kind=icon}
返回
Offline Robust Model Predictive Control for Autonomous Vehicle Steering Systems Using LMI-Based Optimization
.png){kind=icon}
PRE
AI
DOI：10.1002/rnc.70422.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The well-known offline robust model predictive control (RMPC) effectively addresses uncertain parameters for autonomous vehicle systems. However, it requires memory to save the variable and more computation time to search the lookup table to find the best values of the weighting matrices. To address these issues, this article introduces a new offline RMPC approach for enhancing the steering control of autonomous vehicles (AVs) using linear matrix inequality (LMI) optimization that can eliminate storing variables and lookup tables. In order to effectively handle the potential uncertainties associated with the vehicle system parameters, such as total vehicle mass, front and rear cornering stiffness, and varying vehicle speeds by confining them within a defined polytope. By utilizing the polytopic uncertainty method, the offline RMPC is designed to handle a wide range of parameter variations within the defined polytope. Specifically, by defining the upper bound of the cost function as a quadratic form, an offline RMPC method is directly designed, resulting in a significant reduction in the computation burden. Moreover, optimal control is designed by solving an optimization problem based on LMI, allowing the use of efficient convex optimization algorithms. Input and output constraints are enforced to guarantee the safe operation of the AV system in complex and dynamic environments. Finally, the simulation results are presented and compared with the existing studies to demonstrate the effectiveness of our approach. Additionally, co-simulation based on Matlab and Simulink and CarSim software were also conducted to further verify the proposed method. The results show that all state variables satisfy the enforced constraints, and both the path-tracking trajectory performance and execution time are better than those of recent research.
Keyword:
autonomous vehicles
linear matrix inequalities
model uncertainty
robust model predictive control
steering control
期刊
IF:
3.2
论文数:
7.0K
被引数:
1.4W
机构
引用论文
Disturbance Observer-Based Robust Model Predictive Control for a Voltage Sensorless Grid-Connected Inverter With an LCL Filter基于扰动观测器的LCL型无电压传感器并网逆变器鲁棒模型预测控制.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏Robust Tube-Based Model Predictive Control for Lane Change Maneuver of Tractor-Trailer Vehicles Based on a Polynomial Trajectory基于多项式轨迹的牵引车换道鲁棒模型预测控制
PREAI
分享收藏Model-Predictive-Control-Based Path Tracking Controller of Autonomous Vehicle Considering Parametric Uncertainties and Velocity-Varying考虑参数不确定性和速度变化的基于模型预测控制的自主车辆路径跟踪控制器
PREAI
分享收藏Autonomous vehicles: challenges, opportunities, and future implications for transportation policiesOAAI
OAAI分享收藏Output feedback model predictive control for LPV systems based on quasi-min-max algorithm基于准min-max算法的LPV系统输出反馈模型预测控制AUTOMATICA
AUTOMATICAIF5.9
PREAI
分享收藏Robust output feedback model predictive control using off-line linear matrix inequalities基于离线线性矩阵不等式的鲁棒输出反馈模型预测控制
PREAI
分享收藏
查看更多内容