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To the strong nonlinearity and parameter uncertainty in robot manipulator control, a novel self-adaptive PID controller based on RBF neural network on-line identification for the robot manipulator is proposed in this paper, which has solved the weak adaptive ability and poor robustness of the conventional PID control. The control scheme designed in this paper is realized by two kinds of neural networks,...
Because the flight simulator works in different environment for simulating various flight attitudes, the different control algorithm is used for improving the dynamic and static performance. The neural network has good self-learning and self-adaptive, and PID has good robustness, so the adaptive controller based on neural network and PID is used to overcome the coupling inertia and imbalance torque...
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