摘要
以漂浮基柔性关节空间机械臂为研究对象,在空间机械臂系统模型参数未知且存在外部干扰的情况下,结合系统动量守恒和拉格朗日方程建立了系统动力学方程,利用奇异摄动理论将系统分解为快变子系统和慢变子系统。设计了一种利用改进遗传算法(GA)优化神经网络权值的径向基函数神经网络自适应控制器,通过李雅普诺夫稳定性分析和MATLAB数值仿真分析,证实了所设计的控制器能够确保控制系统在更短的时间内达到稳定,并能够同时保证漂浮基柔性关节空间机械臂关节角和关节角速度均获得高精度的轨迹跟踪。
Taking the free-floating flexible joint space manipulator as the research object,the system dynamics equations are established by combining the momentum conservation of the system and the Lagrange equation under the condition that the model parameters of the space manipulator system are unknown and external disturbance exists.Using singular perturbation theory,the system is decomposed into fast-changing subsystems and slow-changing subsystems.A radial basis function neural network adaptive controller using improved genetic algorithm(GA)to optimize neural network weights is designed.Through Lyapunov stability analysis and MATLAB numerical simulation analysis,it is confirmed that the designed controller can ensure that the control system reaches stability in a shorter time,and can simultaneously ensure that both the joint angle and the joint angular velocity of the free-floating flexible joint space manipulator get high-precision trajectory tracking.
作者
万博威
陈力
Wan Bowei;Chen Li(School of Mechanical Engineering and Automation, Fuzhou University, Fujian Fuzhou, 350108, China)
出处
《机械设计与制造工程》
2020年第3期35-38,共4页
Machine Design and Manufacturing Engineering
基金
国家自然科学基金资助项目(11372073)。
关键词
柔性关节
空间机械臂
神经网络
奇异摄动理论
遗传算法
flexible-joint
space manipulator
neural network
singular perturbation theory
genetic algorithm
