摘要
对具有量测噪声、模型噪声和输入信号干扰的四轮移动机器人轨迹跟踪的最优状态反馈控制进行研究.建立系统的运动学与动力学方程和轨迹生成方程,导出了相应的离散状态方程式,采用卡尔曼滤波器对伴有高斯白噪声的系统状态方程进行了状态估计,提出一种基于李亚普诺夫稳定性的最优状态反馈控制策略.给出了补偿输入信号干扰的自适应算法.仿真结果表明,所提出的控制算法,在四轮移动机器人轨迹跟踪中,能有效地抑制系统的模型、量测和输入信号中的随机噪声和扰动,提高系统的跟踪精度和动态响应速度,使系统具有优良的静、动态特性.
Optimal state feedback control was studied for trajectory tracking control of a four-wheel mobile robot in the presence of measure noise, model noise and input signal noise. The kinematic and dynamic model and the trajectory generation of the omnidirectional vehicle were established. The discrete state equations were derived. Then an optimal state feedback controller based on Lyapunov stability using the Kalman filter state with white noises estimation technique was derived. A self-adaptive control algorithm was presented to compensate for the effects of input signal noise. Simulation results demonstrate that the model measurement and input signal noises and disturbances of the system can be effectively compensated; the tracking precision and dynamic response speed of the system can be obviously increased.
出处
《浙江大学学报（工学版）》
EI
CAS
CSCD
北大核心
2009年第12期2186-2190,共5页
Journal of Zhejiang University：Engineering Science
基金
国家自然科学基金资助项目(60405012)
