基于状态空间估计和卡尔曼滤波的车辆牵引直流电机转矩控制

Alex Archela, Dário Guilherme Toginho, L. F. Melo
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引用次数: 4

摘要

电动汽车和移动机器人的牵引控制技术得到了广泛的研究。本文对用于移动车辆牵引的直流电动机转矩控制与经典速度控制器进行了比较研究。给出了一种通用电机参数估计方法和直流电机离散模型状态空间方程。本文还介绍了实现该系统所使用的硬件。作为控制反馈的一部分,电机产生的电磁转矩不是由扭矩传感器读取,而是由卡尔曼滤波估计器估计,给定连接到电机轴的霍尔效应传感器系统读取的速度。该系统全部在硬件在环系统上进行仿真,其中参数可以同时调整到运行系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Torque Control of a DC Motor With a State Space Estimator and Kalman Filter for Vehicle Traction
The control techniques for traction of electric vehicles and mobile robotics has been extensively studied. This paper presents a comparative study over torque control of a DC motor against classical speed controllers, for use on traction of mobile vehicles. Also it presents an approach to estimate the parameters of a generic motor and the equations for discrete model state space of a DC motor. It is also described in this paper the hardware used for implementation of the system. As part of the controlled feedback the electromagnetic torque generated by the motor is not read by a torque sensor, but estimated by a Kalman filter estimator, given the speed read by a Hall effect sensor system connected to the shaft of the motor. The system is all simulated on a hardware-in-the-loop system, where the parameters can be adjusted simultaneously to a running system.
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