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A Nonlinear H-infinity Control Approach for Autonomous Truck and Trailer Systems

机译:自主卡车和拖车系统的非线性H无限控制方法

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摘要

A nonlinear optimal control method is developed for autonomous truck and trailer systems. Actually, two cases are distinguished: (a) a truck and trailer system that is steered by the front wheels of its truck, (b) an autonomous fire-truck robot that is steered by both the front wheels of its truck and by the rear wheels of its trailer. The kinematic model of the autonomous vehicles undergoes linearization through Taylor series expansion. The linearization is computed at a temporary operating point that is defined at each time instant by the present value of the state vector and the last value of the control inputs vector. The linearization is based on the computation of Jacobian matrices. The modeling error due to approximate linearization is considered to be a perturbation that is compensated by the robustness of the control scheme. For the approximately linearized model of the autonomous vehicles an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. The stability of the control loop is confirmed through Lyapunov analysis. It is shown that the control loop exhibits the H-infinity tracking performance which implies elevated robustness against modeling errors and external disturbances. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven. Finally, to implement state estimation-based control for the autonomous vehicles, through the processing of a small number of sensor measurements, the H-infinity Kalman Filter is proposed.
机译:针对自主卡车和拖车系统,开发了一种非线性最优控制方法。实际上,有两种情况是有区别的:(a)由卡车的前轮操纵的卡车和拖车系统,(b)由卡车的前轮和后轮操纵的自主式消防车机器人拖车的轮子。自主车辆的运动学模型通过泰勒级数展开进行线性化。线性化是在每个时间瞬时由状态向量的当前值和控制输入向量的最后一个值定义的临时工作点上计算的。线性化基于雅可比矩阵的计算。归因于近似线性化的建模误差被认为是由控制方案的鲁棒性所补偿的扰动。对于自动驾驶汽车的近似线性化模型,设计了H无穷大反馈控制器。这需要在控制算法的每次迭代中求解代数Riccati方程。控制回路的稳定性通过Lyapunov分析得到确认。结果表明,控制回路表现出H无限跟踪性能,这意味着对建模误差和外部干扰的鲁棒性增强。此外,在适度的条件下,证明了控制回路的全局渐近稳定性。最后,为了实现对自动驾驶汽车的基于状态估计的控制,通过处理少量传感器测量值,提出了H-无限卡尔曼滤波器。

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