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Linear time-varying model predictive control and its application to active steering systems: Stability analysis and experimental validation

机译:线性时变模型预测控制及其在主动转向系统中的应用:稳定性分析和实验验证

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A model predictive control (MPC) approach for controlling an active front steering (AFS) system in an autonomous vehicle is presented. At each time step a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to best follow the desired trajectory on slippery roads at the highest possible entry speed. We start from the results presented in (Int. J. Veh. Auton. Syst. 2005; 3(2-4):265-291; IEEE Trans. Contr. Syst. Technol. 2007; 15(3)) and formulate the MPC problem based on successive online linearization of the nonlinear vehicle model (linear time-varying (LTV) MPC). We present a sufficient stability condition for such LTV MPC scheme. The condition is derived for a general class of nonlinear discrete time systems and results into an additional convex constraint to be included in the LTV MPC design. For the AFS control problem, we compare the proposed LTV MPC scheme with the LTV MPC scheme in (IEEE Trans. Contr. Syst. Technol. 2007; 15(3)) where stability has been enforced with an ad hoc constraint. Simulation and experimental tests up to 17 m/s on icy roads show the effectiveness of the LTV MPC formulation. Copyright (c) 2007 John Wiley & Sons, Ltd.
机译:提出了一种模型预测控制(MPC)方法,用于控制自动驾驶汽车中的主动前转向(AFS)系统。在每个时间步长上,假定轨迹在有限的水平范围内都是已知的,并且MPC控制器计算前转向角,以便在滑行道路上以尽可能高的进入速度最佳地遵循所需的轨迹。我们从(Int。J. Veh。Auton。Syst。2005; 3(2-4):265-291; IEEE Trans.Contr.Syst.Technol。2007; 15(3))中介绍的结果开始,并制定出MPC问题基于非线性车辆模型的连续在线线性化(线性时变(LTV)MPC)。我们为这种LTV MPC方案提供了充分的稳定性条件。该条件是针对一般类别的非线性离散时间系统导出的,并导致附加的凸约束要包含在LTV MPC设计中。对于AFS控制问题,我们将提出的LTV MPC方案与(IEEE Trans。Contr。Syst。Technol。2007; 15(3))中的LTV MPC方案进行了比较,其中已通过临时约束实施了稳定性。在结冰的道路上高达17 m / s的仿真和实验测试表明LTV MPC配方的有效性。版权所有(c)2007 John Wiley&Sons,Ltd.

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