摘要： 针对机器人建模时,需要同时控制倾角和速度的问题,在建立两轮巡检机器人数学模型的基础上,设计线性二次型调节(LQR)控制器对机器人的倾角和速度进行控制,并分析整个系统的稳定性,得到系统稳定的条件。在两轮巡检机器人实际控制过程中,机器人倾角的测量不可避
免地受到系统噪声和积分误差的影响,为此,引入卡尔曼滤波算法对加速度计和陀螺仪采集到的信号进行融合,以实时得到准确的机器人倾角信号。在Matlab-Simulink软件平台和机器人实物平台对机器人系统进行LQR控制算法实验。结果表明,基于卡尔曼滤波和LQR算法,机
器人能按照指定的速度匀速直立行走,且具有较好的抗干扰能力。
关键词:
线性二次型调节算法,
稳定性分析,
卡尔曼滤波,
Matlab-Simulink仿真,
实时控制
Abstract: In order to control the dip angle and speed of the robot simultaneously on robot modeling,based on the mathematical models of two-wheeled patrol robot,Linear Quadratic Regulator(LQR) controller is designed for the system.The condition for system stability is developed so that the proper control parameters can be chosen to guarantee the whole system stability.In actual application,Kalman filtering algorithm is used to acquire dip angle by fusing data from the accelerometer and the gyroscope.The simulation in Matlab-Simulink platform and real-time control in real robot platform experiments result show that based on Kalman filtering and LQR algorithm,the two-wheeled robot can run erectly at the specified speed and has strong anti-interference performance.
Key words:
Linear Quadratic Regulator(LQR) algorithm,
stability analysis,
Kalman filtering,
Matlab-Simulink simulation,
real-time control
中图分类号:
胡凌燕,徐源春,徐少平,刘小平,谢志强. 基于卡尔曼滤波和线性二次型调节的两轮巡检机器人[J]. 计算机工程.
HU Lingyan,XU Yuanchun,XU Shaoping,LIU Xiaoping,XIE Zhiqiang. Two-wheeled Patrol Robot Based on Kalman Filtering and Linear Quadratic Regulation[J]. Computer Engineering.