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For the attitude control of the inverted pendulum, a new kind of intelligent method is proposed in this paper. The learning method consists of several steps: states and motions division, motion choosing, mapping relationship updates and etc. In the learning method, the state ideality is defined to help evaluate how good the state is. The concept of curiosity is introduced to the motion choosing to trade-off between exploitation and exploration. A learning mechanism is designed to decide the learning direction. Simulation results show that the learning method is with the properties of self-learning and self-organizing. Comparation with the LQR(Linear Quadratic Regulator) method under the same disturbance shows that such a learning method is more robust. © 2017 IEEE.
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