Adaptive PID Control Based on Improved BP Neural Network

摘要：

An improved Back Propagation Neural Network (BPNN)based on self-leaning adaptive PID control strategy is presented in this paper. With the learning of a BPNN controller, it gradually compensates the deficiency of the feedback PID controller, until they gradually control the system together perfectly. The design of the controller is independent on the empirical knowledge of the system, and the parameters are tuned based on the testing information and error feedback-learning algorithm. The results of the simulation show that the proposed controller has the adaptability, strong robustness and satisfactory control performance in the nonlinear and time varying system.

关键词： Back Propagation (BP) Neural Network Adaptive PID control Simulation

作者: Ming-hui Qiang Ming-guang Zhang

作者单位: School of Electrical and Information Engineering, Lanzhou University of Technology Lanzhou,Gansu 730050, China

会议类型: 国际会议

会议名称: 2006 International Symposium on Distributed Computing and Applications to Business,Engineering and Science(2006年国际电子、工程及科学领域的分布式计算应用学术研讨会)

会议地点: 杭州

会议语种:英文

页码: 979-981

在线出版日期: 2006-10-12（万方平台首次上网日期，不代表论文的发表时间）