Research on intelligent anti-Swing control of bridge crane based on Fuzzy self-tuning PID control--《Journal of Huainan Normal University》2012年03期
Research on intelligent anti-Swing control of bridge crane based on Fuzzy self-tuning PID control
HU Yan-li,LIU Tuan-jie,JIA Qun,SHEN Xiao-bo
In order to promptly stop load swing and precisely position the trolley of bridge crane,further to improve the efficiency of cranes,many scholars at home and abroad have done a lot of studies for anti-swing control methods.This paper designs a fuzzy self-tuning PID controller based on nonlinear mathematical model of bridge crane.In the controller,the position loop takes use of fuzzy PID controller,the angle loop takes use of fuzzy controller.The MATLAB simulation shows the feasibility of the method compared with the LQR,the control process is more stable and the control accuracy is higher.Moreover,the system has better robustness and good performance when load mass and rope length change.
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TH215;TP273.4
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Chinese Journal Full-text Database
CAO Wen-xia1,WANG Yong-hua1,QIAN Duo-de2(1.Department of Mechanical Engineering,Anhui Technical College of Water Resources and Hydroelectric Power,Hefei .R&D center,Anhui Jianghuai Automobile Co.,Ltd,Hefei 230601);[J];Journal of Anhui Agricultural U2012-01
WU Wen-jin(School of Physics and Electrical Engineering,Anqing Teachers of College,Anqing 246133,China);[J];Journal of Anqing Teachers College(Natural Science Edition);2010-01
WU Wen-jin1,2,LI Yan-mei1(1.School of Physics and Electrical Engineering of Anqing Teachers College,Anqing,Anhui 246133,C 2.The school of electrical engineering and automation,HeFei University of Technology,Hefei 230009,China);[J];Journal of Anqing Teachers College(Natural Science Edition);2012-01
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Solving Traveling Salesman Problem Using Combination Intelligent Techniques and Genetic Algorithm
Behrooz Ameri Shahrabi, Samane Hosseinmardi, Mohammad Ebrahim Shiri Ahmad Abadi
Various methods have been proposed to solve the traveling salesman problem such as a solution based on genetic algorithm. But in general, these algorithms and especially genetic algorithm are often faced with early convergence in solving combinatorial problem, in this paper we review and introduce new methods and survey to solve the problem. Our idea based on hybrid genetic algorithm for solving the traveling salesman problem. The implementation of our algorithm is that different methods at each step of the algorithm, including initial population by the nearest neighbor, greedy algorithm and combination of them with the genetic algorithm and also different methods for mutation operator has been surveyed. Combining untwist algorithm with genetic algorithm to improve the population and is expected to strengthen the global optimal solution. When the diversity of the population is reduced, artificial chromosomes with high diversity level are introduce to increase the diversity level in the system .Implementation has been shown the improvement result of hybrid algorithm than the pure genetic algorithm .
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