Title :
Position Control of a Intelligent Module based on Neural Network Sliding Mode Control
Author :
Chen, Weihai ; Yong, Gao ; Lu, Zhen ; Yuan, Xue Ming
Author_Institution :
Singapore Inst. of Manuf. Technol., Singapore
Abstract :
Based on the standard intelligent module of the modular robot, a kind of neural network sliding mode control method is put forward. The neural network is used to approach to the function between the state hyperplane of the system and the reaching law. A hyperbolic tangent function is applied to replace the saturated function in order to realize the boundary method design of the sliding mode control. Simulation results show that system owns quick response and strong antijamming capability. Moreover, the chattering of neural network sliding mode control is weakened effectively, and problems that cannot be solved with the traditional PID control method under complicated environment and conditions such as variable load etc can be solved.
Keywords :
intelligent robots; neurocontrollers; position control; three-term control; variable structure systems; PID control method; antijamming capability; boundary method design; hyperbolic tangent function; intelligent module; modular robot; neural network sliding mode control; position control; state hyperplane; Automatic voltage control; Intelligent control; Intelligent networks; Neural networks; Position control; Robot sensing systems; Service robots; Servomotors; Sliding mode control; Torque control; Robot control; actuator; neural network control; sliding-mode control;
Conference_Titel :
Industrial Informatics, 2006 IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
0-7803-9700-2
Electronic_ISBN :
0-7803-9701-0
DOI :
10.1109/INDIN.2006.275732