ROTOR SPEED IDENTIFICATION ON DTC SYSTEM BASED ON NEURAL NETWORK OF NEW CHAOS OPTIMIZER ALGORITHMS

摘要：

To solve the disadvantage that BP neural network is liable to get into the local minimum, a novel learning algorithm that new chaos optimizer BP neural network is proposed. By the use of the properties of ergodicity and randomness of chaos algorithms, and combining global rough search and local elaborate search of chaotic variable, get the global optimization weight values of neural network. By the simulation of Direct Torque Control (DTC) system based on new chaos neural network, the simulation results show that the rotor speed identification has high approximation precision and good generalization capability, and provides a new plan for the speed-sensorless DTC system.

关键词： Chaos optimization algorithm BP neural network DTC Rotor speed identification

作者: CHENG-ZHI CAO WEN-JING WANG FENG-KUN LI

作者单位: School of Information Science and Engineering,Learning Center, Shenyang University of Technology, Shenyang 110023, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 824-828

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）