执行器受限空间机器人的模糊神经网络控制

FUZZY NEURAL NETWORK CONTROL FOR A SPACE-BASED ROBOT WITH CONSTRAINED ACTUATORS

  • 摘要: 空间机器人关节执行器输出力矩幅值及幅值变化率受限的情况,是其在太空应用中不可避免要面临的实际问题。为此该文讨论了关节执行器输出力矩幅值及幅值率受限情况下参数未知空间机器人系统协调运动的动力学控制问题。依据系统动量守恒关系和拉格朗日第二类方程,推导了漂浮基空间机器人系统的动力学方程。以此为基础,针对关节执行器输出力矩幅值及幅值率受限的情况,设计了一种自适应模糊神经网络控制器,以使空间机器人系统的本体姿态和机械臂关节铰协调地跟踪各自在关节空间的期望运动轨迹。该控制方案由自适应模糊神经网络控制器及抗饱和参数自适应律构成。首先利用有限差分法将幅值率受限条件转化为幅值受限条件,并与该文预设的力矩受限条件比较以确定每个采样时刻的力矩动态受限范围;然后再通过设计一个抗饱和参数自适应律来确保执行器的输出力矩在动态受限范围内。基于Lyapunov稳定性理论证明了该控制器可确保控制系统是渐近稳定的。仿真对比实验证明了该控制方案的有效性。

     

    Abstract: A situation in which a robot’s joint actuator torque amplitude and amplitude rate outputs are constrained is an actual problem which could be faced in space applications. This paper discusses a dynamics control problem for coordinated movement of an unknown parameter space robot system, under joint actuator torque amplitude and amplitude rate saturation constraints. According to linear momentum conversation and the Lagrange approach, a dynamic equation for a free-floating space robot system is developed. Based on it, a control scheme using an adaptive fuzzy neural network is proposed, which contraposes the joint actuator output torque’s amplitude and the saturation constraints of its rate to control the desired trajectory of the joint hinge to follow the expected movement track of the space robot system. Said control scheme is combined with an adaptive fuzzy neural network controller and an anti-saturation parameter adaptive law. Firstly, the finite difference approximation is used to transform an amplitude rate saturation constraint condition into an amplitude saturation constraint condition, which is compared with a torque limiting condition which been set in advance in this paper, ensuring a limited range of torque trends in every sampling moment, thus guaranteeing that the output torque of the actuator is within the dynamic limited range by designing an anti-saturation parameter adaptive law. Based on the stability theory of Lyapunov, it proves said controller may ensure that the control system is asymptotically stable. Simulation comparison experiments testify to the effectiveness of this control scheme.

     

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