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Research of attitude stability control technology for photoelectric detection system based on CMAC

WEI Guo-feng;GUO Shao-wen;XU Ying;LI Wei;CHEN Xi;WANG Rui;College of Electromechanical Engineering,Heilongjiang Institute of Technology;  
The cerebellar model articulation controller(CMAC)neural network is applied to the design for photoelectric stable tracking control system of motorial carrier,respectively constructing "CMAC network learning algorithm"and "CMAC control network".The generalization parameter is 4,and the learning algorithmδis used to adjust to the network weights.In order to assess the approximation ability of the CMAC network to built a target system,a nonlinear system is selected as the object.The input signal is continuous square wave and simulated.The simulation data shows that the input signal has changed after 0.15 seconds and the steady-state error of the output signal is 0.Using DC torque motor and resolution of 767×10-6 rad of photoelectric encoder,it builds a three-axis attitude stability control experimental device of motorial carrier.The result shows that controller based on CMAC neural network is constructed which can realize attitude stabilization error as 870×10-6 rad in this experiment device.
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