Study on PID controller based on fuzzy RBF neural network in rolling mill hydraulic AGC system

Zhang, Yong; Lv, Huichao

doi:10.1109/ccdc.2016.7531817

Cited by 3 publications

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The chaos has been a kind of novel global optimization technique. People pay much attention to the research of the Journal of Sensors optimization method based on the chaotic search [29,31,36,38]. At present, some scholars have applied it to the optimization of neural network weights and achieved good results.…”

Section: Offline Tuning Based On the Cpsomentioning

confidence: 99%

See 1 more Smart Citation

Parameter Optimization on FNN/PID Compound Controller for a Three-Axis Inertially Stabilized Platform for Aerial Remote Sensing Applications

et al. 2019

View full text Add to dashboard Cite

This paper presents a composite parameter optimization method based on the chaos particle swarm optimization and the back propagation algorithms for a fuzzy neural network/proportion integration differentiation compound controller, which is applied for an aerial inertially stabilized platform for aerial remote sensing applications. Firstly, a compound controller combining both the adaptive fuzzy neural network and traditional PID control methods is developed to deal with the contradiction between the control precision and robustness due to disturbances. Then, on the basis of both the chaos particle swarm optimization and the back propagation compound algorithms, the parameters of the fuzzy neural network/PID compound controller are optimized offline and fine-tuned online, respectively. In this way, the compound controller can achieve good adaptive convergence so as to get high stabilization precision under the multisource dynamic disturbance environment. To verify the method, the simulations are carried out. The results show that the composite parameter optimization method can effectively enhance the convergence of the controller, by which the stabilization precision and disturbance rejection capability of the proposed fuzzy neural network/PID compound controller are improved obviously.

show abstract

Section: Offline Tuning Based On the Cpsomentioning

confidence: 99%

“…Corresponding to the ISP system, the number of the nodes of the fuzzy rule layer is 49, and the method of fuzzy inference is as follows [36]:…”

mentioning

confidence: 99%

Parameter Optimization on FNN/PID Compound Controller for a Three-Axis Inertially Stabilized Platform for Aerial Remote Sensing Applications

et al. 2019

View full text Add to dashboard Cite

show abstract

Fuzzy Neural Network PID Control of Quadrotor Unmanned Aerial Vehicle Based on PSO-GA Optimization

Zhang

Zheng

et al. 2019

Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019)

View full text Add to dashboard Cite

RBF Neural Network Sliding Mode control for Aeronautical Remote Sensing Stable Platform

Wang

Gao

et al. 2020

2020 Chinese Automation Congress (CAC)

View full text Add to dashboard Cite

Study on PID controller based on fuzzy RBF neural network in rolling mill hydraulic AGC system

Cited by 3 publications

References 2 publications

Parameter Optimization on FNN/PID Compound Controller for a Three-Axis Inertially Stabilized Platform for Aerial Remote Sensing Applications

Parameter Optimization on FNN/PID Compound Controller for a Three-Axis Inertially Stabilized Platform for Aerial Remote Sensing Applications

Fuzzy Neural Network PID Control of Quadrotor Unmanned Aerial Vehicle Based on PSO-GA Optimization

RBF Neural Network Sliding Mode control for Aeronautical Remote Sensing Stable Platform

Contact Info

Product

Resources

About