文献类型：期刊文献

英文题名：Wireless networked learning control system based on Kalman filter and biogeography-based optimization method

作者：Ma, Haiping[1,2];Fei, Minrui[1];Yang, Zhile[3];Wang, Haikuan[1]

机构：[1]Shanghai Univ, Shanghai Key Lab Power Stn Automat Technol, Sch Mechatron Engn & Automat, Shanghai, Peoples R China;[2]Shaoxing Univ, Dept Phys & Elect Engn, Shaoxing, Zhejiang, Peoples R China;[3]Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT7 1NN, Antrim, North Ireland

年份：2014

卷号：36

期号：2

起止页码：224

外文期刊名：TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL

收录：SCI-EXPANDED(收录号：WOS:000333323800009)、、EI(收录号：20141817669473)、Scopus(收录号：2-s2.0-84899080822)、WOS

基金：This work is supported by the National Natural Science Foundation of China under grant number 61074032, the Zhejiang Provincial Natural Science Foundation of China under grant number Y1090866, and the Project of Science and Technology Commission of Shanghai Municipality under grant number 10JC1405000.

语种：英文

外文关键词：Biogeography-based optimization; networked learning control system; wireless network; Kalman filter; power generation system

外文摘要：This paper proposes a biogeography-based optimization (BBO) method augmented with a Kalman filter, which is called KFBBO, for PID parameter tuning in a wireless networked learning control system (WNLCS). Because of unreliable transmission of data and commands in wireless networks, the control system is noisy and prone to errors, which results in poor performance by the conventional PID method for wireless networked control in real-world applications. BBO as a new evolutionary optimization is proposed to solve this problem by dynamically optimizing the PID control parameters. Because the wireless network environment is noisy, we also use a Kalman filter to counteract the negative effects of noise and to improve the optimization ability of BBO. Simulation experiments are conducted to evaluate our proposed KFBBO, and the results indicate that the control performance obtained by the improved PID method is better than the conventional PID method. Furthermore, this proposed method is applied to a steam turbine power generation system based on a WNLCS, and the results show its feasibility and effectiveness.