Stabilizing Two-wheeled robot using linear quadratic regulator and states estimation

N. Uddin, Teguh Aryo Nugroho, Wahyu Agung Pramudito
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引用次数: 9

Abstract

A control design for two-wheeled robot (TWR) stabilization using linear quadratic regulator (LQR) method and states estimation is presented. A two-wheeled robot is an unstable system such that a control system is required to stabilize it. LQR is a control design method where the control gain is calculated by minimizing a performance index. The LQR method results in a full states feedback control law. Applying the LQR method for TWR stabilization will require feedback from pitching angle and pitching rate angle measurements. However, the common available sensor in the TWR is only a rate gyro which measures the pitching rate angle. Theoretically, time integration of the pitching rate angle results in pitching angle but it is not practically applicable because the time integration of measurement data may result in an accumulation of error and noise. Instead of the time integration, a Luenberger observer is applied to estimate the pitching angle based on the pitching rate angle measurement. Simulations of the TWR stabilization using the designed controller are presented through two scenarios: 1) both required state feedback are assumed to be available, and 2) both required state feedback are obtained through estimation using Luenberger observer. The first scenario is representing an ideal condition, while the second scenario is representing a practical condition. Simulation results show that the TWR is stabilized for the both scenarios, where the control system performance in the second scenario is slightly less than the first scenario but still acceptable.
利用线性二次型调节器和状态估计稳定两轮机器人
提出了一种基于线性二次型调节器(LQR)和状态估计的两轮机器人(TWR)镇定控制设计。两轮机器人是一个不稳定的系统,需要一个控制系统来稳定它。LQR是一种控制设计方法,其中控制增益是通过最小化性能指标来计算的。LQR方法得到了一个全状态反馈控制律。将LQR方法应用于TWR稳定需要俯仰角和俯仰速率角测量的反馈。然而,TWR中常用的传感器只是测量俯仰速率角的速率陀螺仪。理论上,对俯仰速度角进行时间积分得到俯仰角,但由于测量数据的时间积分可能导致误差和噪声的积累,因此在实际应用中并不适用。在俯仰速率角测量的基础上,采用Luenberger观测器来估计俯仰角,而不是时间积分。利用所设计的控制器对TWR稳定化进行了仿真:1)假设两个所需状态反馈都是可用的,2)两个所需状态反馈都是通过Luenberger观测器估计得到的。第一个场景代表理想情况,而第二个场景代表实际情况。仿真结果表明,两种情况下的TWR都是稳定的,其中第二种情况下的控制系统性能略低于第一种情况,但仍然可以接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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