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使用移动时域估计对配备增量编码器的广义N - 拖车车辆进行绝对关节角度估计。

Absolute joint-angle estimation of Generalised N-Trailer vehicles equipped with incremental encoders using moving horizon estimation.

作者信息

Deniz Nestor, Jorquera Franco, Cheein Fernando Auat

机构信息

Electronics Engineer Department, Universidad Tecnica Federico Santa Maria, Valparaiso, 2390123, Chile.

Electronics Engineer Department, Universidad Tecnica Federico Santa Maria, Valparaiso, 2390123, Chile.

出版信息

ISA Trans. 2023 Dec;143:678-691. doi: 10.1016/j.isatra.2023.09.004. Epub 2023 Sep 8.

DOI:10.1016/j.isatra.2023.09.004
PMID:37730463
Abstract

The Generalised N-Trailer (GNT) vehicle is a tool for field operations that optimises harvesting and transportation tasks, offering a highly scalable payload using only one tractor. Precise knowledge of the position and attitude of each segment in the chained vehicle is crucial for the controller's success during operation. In this study, we propose the use of a Nonlinear Moving Horizon Estimator (NMHE) to estimate the system's state when the GNT vehicle is equipped with incremental encoders on its joints. A first NMHE serves as a virtual calibration procedure, estimating initial joint angle values and the system's state using noisy and biased measurements of the joints and the tractor pose. This calibration is performed while the chained vehicle travels along a straight path, whose length is determined by the number of trailers and their geometrical properties. Subsequently, a second NMHE, with fewer optimisation variables and constraints replace the first to effectively reduce the computational burden. Moreover, it treats the incremental encoder measurements as if they were absolute encoders after the initial joint angles have been estimated by the first NMHE. The proposed method is compared against the Extended Kalman Filter (EKF) and validated through simulated and practical real-time experiments, showcasing its effectiveness in achieving precise control and enhancing operational efficiency.

摘要

广义N型挂车(GNT)车辆是一种用于野外作业的工具,它优化了收割和运输任务,仅使用一台拖拉机就能提供高度可扩展的有效载荷。对于链式车辆中每个部分的位置和姿态的精确了解,对于控制器在操作过程中的成功至关重要。在本研究中,我们提出在GNT车辆的关节上配备增量编码器时,使用非线性移动时域估计器(NMHE)来估计系统状态。第一个NMHE用作虚拟校准程序,利用关节和拖拉机姿态的噪声和有偏测量来估计初始关节角度值和系统状态。该校准在链式车辆沿直线路径行驶时进行,路径长度由挂车数量及其几何特性决定。随后,具有较少优化变量和约束的第二个NMHE取代第一个,以有效减轻计算负担。此外,在第一个NMHE估计出初始关节角度后,它将增量编码器测量值视为绝对编码器测量值。将所提出的方法与扩展卡尔曼滤波器(EKF)进行比较,并通过模拟和实际实时实验进行验证,展示了其在实现精确控制和提高运行效率方面的有效性。

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