Academic Journal of Computing & Information Science, 2021, 4(3); doi: 10.25236/AJCIS.2021.040303.
Keju Wang, Xuxiu Zhang, Lina Bai
School of Dalian Jiaotong University, Liaoning China
Aiming at the network control system with time delay and packet loss, this paper designs a fuzzy adaptive PID controller to realize the adjustment of the network control system. Through the design of wavelet neural algorithm to predict the time delay, the fuzzy adaptive PID can realize the online adjustment of Kp, Ki and Kd, which overcomes the problem of constant input parameter adjustment of the traditional PID controller. Fuzzy control is realized by designing fuzzy rules, and finally through comparison The Matlab simulation renderings of traditional PID controller and fuzzy adaptive PID controller show that the robustness and accuracy of fuzzy adaptive PID controller are better.
Network control system, fuzzy adaptive PID controller, wavelet neural network, time delay
Keju Wang, Xuxiu Zhang, Lina Bai. Wavelet Neural Network Control System Based on Fuzzy PID. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 3: 18-24. https://doi.org/10.25236/AJCIS.2021.040303.
 Lu Qing. Research on predictive control of networked control systems [D]. Bohai University, 2016.
 Wu Jie, Fu Jingqi. Collaborative design of event triggering and quantitative control for networked control systems [J]. Electronic Measurement Technology, 2017, 40(05): 80-86.
 Tang Xiaoming, Deng Li, Yu Jimin, et al. Output feedback predictive control of networked control system based on interval two T-S fuzzy model [J]. Acta Automatica Sinica, 2019, v.45 (03): 162-174.
 YING Z, HU S. H infinity control for DC servo motor in the network environment [C] //2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), IEEE, 2015.
 Jing S, Guo S, Zhao X, et al. BP neural network PID controller of pocket dropout [C] // IEEE International Conference on Computer & Communications. IEEE, 2016.
 Duan Kun, Lu Meng. Fuzzy control and fuzzy adaptive PID control of mobile robots [J]. Electronic Test, 2019.
 Wang R, Duan R. Research and Simulation of Network Control System Smith Estimating PSD Control [J]. Journal of Physics: Conference Series, 2021, 1846(1):012085 (8pp).
 FEDOR, Y., CHEMASHKIN, et al. Problems in Network Control Systems and their Solutions [C] //2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), IEEE, 2019.
 Zhang Hao, Peng Chen, Sun Hongtao. Research on the Stability of Multi-path Wireless Network Control System [J]. Journal of Electronic Measurement and Instrument, 2016, 30(11): 1627-1634.
 ZHANG Y, XIE S, REN L, et al. A new predictive sliding mode control approach for networked control systems with time delay and packet dropout [J]. IEEE Access, 2019, PP (99): 1-1.
 Li Junhui, Lu Jieying, Su Weizhou. Mean Square Stabilization Analysis of Network Control System with Random Delay [J]. Control and Decision, 2020, v.35 (04): 178-183.
 Xie Dong, Zhang Xing, Cao Renxian. Island detection technology based on wavelet transform and neural network [J]. Proceedings of the CSEE, 2014, 34(4): 537-544.
 Luo Yongping. Research on Time Delay Prediction and Compensation Control of Network Control System [D]. Zhengzhou University.
 Peng Y, Luo J, Zhuang J, et al. Model reference fuzzy adaptive PID control and its applications in typical industrial processes [C] //2008 IEEE International Conference on Automation and Logistics. IEEE, 2008: 896-901.
 Yao G, Gao F, Wang C, et al. Design and simulation based on Kalman filter fuzzy adaptive PID control for mold liquid level control system [C] //2009 Chinese Control and Decision Conference. IEEE, 2009: 6105-6109.