用杆位控制方法稳定推车倒立摆系统

I. Siradjuddin, Zakiyah Amalia, B. Setiawan, R. Wicaksono, E. Yudaningtyas
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引用次数: 15

摘要

小车倒立摆系统是许多控制算法测试中最常见的例子之一,因为它具有非线性、复杂性和系统模型欠驱动等挑战性问题。事实上,倒立摆的非线性特性是很容易观察到的。在小车中给予相同的速度,可以得到不同的摆角响应。小车倒立摆可以理解为一个欠驱动系统,因为该系统具有比自由度更少的驱动器数量。用拉格朗日方程对倒立摆系统进行建模是最方便的方法之一。然而,目前已有的许多倒立摆模型都是用简化的物理模型推导出来的。这种简化的模型可能会导致控制算法在实际物理倒立摆系统中的实现问题。本文建立了一个倒立摆系统模型,其中在倒立摆模型的推导中包含了机械传动系统模型和电机模型。因此,在实际系统中控制实现的问题可以最小化。利用拉格朗日方程推导了倒立摆的数学模型。讨论了系统极零点的确定问题。提出了一种简单的摆杆放置方法,使摆锤稳定在小车的期望位置。Matlab仿真结果表明了该方法的有效性。然而,这种直观的方法可以让我们更好地理解控制行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stabilising a cart inverted pendulum system using pole placement control method
A cart inverted pendulum system is one of the most common case to be considered for testing many control algorithms, since it has some challenging problems associated with non linearity, complexity and underactuated system model. In fact, non-linearity behaviour of the inverted pendulum can be observed easily. Different pendulum angle response can be obtained by giving the same velocity in the cart. The cart inverted pendulum can be understood as an under actuated system since the system has a lower number of actuator than the degrees of freedom. One of the most convenient method to model the inverted pendulum system is to use Lagrange's equation. However, at present, many presented inverted pendulum models have been derived using simplified physical model. This simplified model may lead to problems for the implementation of the control algorithm in a real physical inverted pendulum system. In this paper, an inverted pendulum system model is presented, where a mechanical transmission system and a motor models have been included in the derivation of the inverted pendulum model. Hence, the problems for the control implementation in a real system can be minimized. The mathematical model of the inverted pendulum was derived using Lagrange's equation. The determination of the pole zero of the system is discussed. A simple method of pole placement is proposed to stabilise the pendulum at the desired position of the cart. Matlab simulation results show the effectiveness of the proposed method. And yet, this intuitive approach can lead to better understanding of the control behaviours.
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