NEURAL NETWORK CONTROL OF UNCERTAINTY ROBOTIC MANIPULATOR WITH H∞ TRACKING PERFORMANCE
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摘要: 针对不确定性机器人提出一种具有H∞跟踪特性的神经网络（NN）控制器，使H∞控制理论与NN有机地结合起来．通过适当选择控制变量加权因子可以使由于NN近似误差以及外部干扰引起的误差动态衰减到期望的程度下．文中基于Lyapunov方法给出了NN学习自适应律，H∞跟踪特性的证明．最后通过在两自由度机器人控制中的应用表明该方案的可行性．Abstract: In this paper, a Neural Network control with H∞ tracking performance for uncertainty robotic manipulator is proposed. The control scheme combined H∞ control theory and NN adptive algorithm organically. If the weight to control variables is appropriatly chosen, the influence of both NN aproximation error and external disturbance can be attenuated to a desired level. Based on Lyapunov method, NN learning law is given and H∞ tracking performance is illustrated. Finally, the developed controller is applied to a two-link robotic manipulator. Simulation results demonstrate that the control scheme is effective.
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Keywords:
- H∞ Tracking control /
- neural network /
- robot
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