摘要
探讨本体位置不控、姿态受控的漂浮基柔性臂空间机器人系统在惯性参数不确定情况下的动力学建模与控制问题。根据系统位置几何关系、动量守恒关系和第二类拉格朗日方程,由假设模态法,建立漂浮基柔性臂空间机器人的系统动力学模型。利用该模型,针对系统惯性参数不确定情况,提出具有L2扰动抑制的刚性运动神经网络L2增益鲁棒控制策略,以使柔性臂空间机器人的本体姿态到达期望位置的同时,机械臂各关节铰能够协调地跟踪关节空间的期望轨迹。为了主动抑制柔性振动,运用虚拟力的概念,构造同时反映柔性模态和刚性运动轨迹的混合期望轨迹,通过改造原有的控制方案,提出基于虚拟力概念的神经网络L2增益鲁棒控制策略。提出控制器的优点在于,既不要求系统动力学方程关于惯性参数呈线性函数关系,也无须预知系统精确的动力学模型;由于运用了虚拟力的概念,从而仅通过设计一个控制输入便可同时保证刚性轨迹跟踪并对柔性振动进行主动抑制,更适应于空间机器人系统的实际应用。理论分析及仿真算例均表明了控制方法的可行性。
Concerned dynamic modeling and control problems are discussed for free-floating flexible arm space robot with uncertain parameters and an uncontrolled base. According to the geometric relationship and law of conversation of momentum, the Lagrange equation of the second kind is utilized to model the dynamic function of the flexible ann space robot incorporating the assumed modes method. By using this model, a neural network L-two-gain robust control scheme with L-two-gain disturbance attenuation is proposed to dominate the base attitude and the joint angle of manipulator to track desired trajectories synchronously in joint space on condition that system parameters are unknown. In order to damp out vibration, conception of virtual force is used to design hybrid desired trajectory which integrate both flexible mode and rigid motion, through transforming the original control scheme and a neural network L-two-gain robust control based on virtual force conception is proposed. The control scheme needs neither linearly parameterize the dynamic equations of the system, nor know any system parameters. Since using the concept of virtual control force, so rigid trajectory track is guaranteed just by inputting one control, and at the same time, active suppression on flexible vibration is made, it＇s more suitable in practical using for space robot system. Theoretical analysis and simulation results verify the feasibility of the proposed control schemes.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2012年第23期23-29,共7页
Journal of Mechanical Engineering
基金
国家自然科学基金(11072061
10672040)
福建省自然科学基金(2010J01003)资助项目
关键词
柔性臂空间机器人
L2扰动抑制
虚拟力
神经网络L2增益鲁棒控制
柔性振动控制
Flexible arm space robot
L-two-gain disturbance attenuation
Virtual force
Neural network
L-two-gain robust control
Actively suppress vibration
