Matrix Inequalities Based Robust Model Predictive Control for Vehicle Considering Model Uncertainties and External Disturbances*

Wenjun Liu, Guang Chen, Alois Knoll
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Abstract

Model uncertainties and external disturbances can inevitably affect vehicle dynamic control accuracy and even cause the vehicle system to be unstable and unsafe. Therefore, vehicle dynamic controller must be able to suppress the influence of model uncertainties and external disturbances on vehicle dynamic control performance. To this aim, we design a matrix inequalities (both bilinear matrix inequalities (BMIs) and linear matrix inequalities (LMIs) are involved) based robust model predictive controller for vehicle dynamic control. Robust positive invariant (RPI) set is used to guarantee the controller is robust and to construct the matrix inequality equations. We test the usefulness of the proposed controller via a numerical example.
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基于矩阵不等式的考虑模型不确定性和外部干扰的车辆鲁棒模型预测控制*
模型的不确定性和外界干扰不可避免地会影响车辆的动态控制精度,甚至导致车辆系统的不稳定和不安全。因此,车辆动态控制器必须能够抑制模型不确定性和外界干扰对车辆动态控制性能的影响。为此,我们设计了一个基于矩阵不等式(双线性矩阵不等式和线性矩阵不等式)的鲁棒模型预测控制器,用于车辆动态控制。利用鲁棒正不变量(RPI)集来保证控制器的鲁棒性,并构造矩阵不等式方程。通过一个数值算例验证了所提控制器的有效性。
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