基于无侧偏角模型匹配方法的主动前转向控制器设计

Mert Sever, M. S. Arslan
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引用次数: 0

摘要

设计了一种无侧偏角模型匹配控制器(MMC),通过主动前转向提高车辆的偏航稳定性。控制器增益的优化是由一个经典的LQR问题指定的。此外,LQR控制器增益的结构使侧滑角无设计。具有结构化控制器增益的LQR的设计是一个受线性矩阵不等式(lmi)约束的凸优化问题。该控制器采用增广状态空间模型,包括线性循环模型和模型匹配误差动力学。通过与经典的全状态反馈LQR的数值比较,证明了该控制器的优越性。以获得切合实际的效果;采用三自由度非线性车辆模型。非线性车辆模型由横向、偏航和纵向运动组成,采用著名的魔术公式轮胎模型。仿真结果表明,所提出的结构化MMC与全状态反馈LQR设计具有良好的兼容性能。
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Active Front Steering Controller Design with Side Slip Angle Free Model Matching Approach
A side slip angle free model matching controller (MMC) is designed to improve vehicle yaw stability by active front steering. Optimization of controller gains is specified by a classical LQR problem. Additionally, LQR controller gains are structured to enable side slip angle free design. Design of an LQR having a structured controller gain is formulated as a convex optimization problem subject to linear matrix inequalities (LMIs) constraints. The proposed controller is designed with an augmented state space model including a linear bicycle model and model matching error dynamics. Superiority of the proposed controller is shown by numerically comparing with a classical full state feedback LQR. In order to obtain realistic results; a three-degrees-of-freedom nonlinear vehicle model is used. The nonlinear vehicle model is composed of lateral, yaw and longitudinal motions with the well-known Magic Formula tire model. Simulation results show that the proposed structured MMC provides very compatible performance with full state feedback LQR design.
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