Title :
Study on Preview Control Theory for Trajectory Tracking Control
Author :
Liu Xiao-feng ; Tian Mu-Qin ; Lv Yong-Wei ; Wang Shu-Hua
Author_Institution :
Taiyuan Univ. of Technol., Taiyuan, China
Abstract :
Trajectory tracking is popularity in industrial procession, such as machining parts control, high automatic control for a roller of shearer cutting in memory mode, etc. In these cases, trajectory tracked was often artificially pre-determined, and essentially belongs to the fields of predictable control. There are still some shortages in the respect of tracking accuracy and responsiveness among the existing control methods. Therefore, the application of predicted control theory, with the neural network and genetic algorithm identifying the dynamic object model, gives new vigor and vitality to the traditional trajectory tracking.
Keywords :
genetic algorithms; neural nets; position control; predictive control; dynamic object model; genetic algorithm; industrial process; neural network; predictable control; preview control theory; trajectory tracking control; Artificial neural networks; Equations; Function approximation; Mathematical model; Target tracking; Training; Trajectory; Auto-adjusting of height for CaiMeiJi; memory cutting; neural network; previewing control;
Conference_Titel :
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-8785-1
DOI :
10.1109/CASoN.2010.105