Drive Controller Based on Fuzzy Sets and Genetic Algorithms
In the field of drive controller, constructing an accurate mathematical model aimed at drive element is an important task as it is closely related to control quality. It is difficult for control systems to produce an accurate mathematical model to meet the desired performance. the sample of the mathematical model in fuzzy design optimization is set up which is to evaluate the performance of controller. Firstly, we obtain a fuzzy model with fast fuzzy clustering, taking into account the information provided by input-output samples. Next, a new control mechanism is developed, which can incorporate conventional controller with inverse predictable compensation. In order to improve the controller effect, the learning method makes use of current data to adjust the online of the fuzzy model, which leads to reveal state transition of systems in real time. As the problem of low efficiency and local optimum caused by traditional optimal methods, this paper adopts Genetic Algorithm to solve the optimization model, So that the optimization process is simplified and global optimum is acquired reliably in Genetic Algorithm.The drive controller test system was introduced.
drive controller fuzzy sets genetic algorithms optimization model
Zhai Ruihong Hu Minhui
School of Architecture and Civil Engineering, Zhejiang University of Science and Technology, Hangzho School of Architecture and Civil Engineering, Zhejiang University of Science and Technology, Hangzho
国际会议
第八届国际测试技术研讨会(8th International Symposium on Test and Measurement)
重庆
英文
2479-2481
2009-08-01（万方平台首次上网日期，不代表论文的发表时间）