Liquid level control of water tank system based on improved polyclonal selection algorithm and RBF network

Author

Zuo, Xiaoming

Author_Institution

Fac. of Mech. Eng., Huaiyin Inst. of Technol. Huaian, Huaiyin, China

Volume

2

fYear

2010

fDate

16-18 April 2010

Abstract

To realize the adaptive control of liquid level of a 2-container water tank system, a novel PID controller based on improved polyclonal selection algorithm and RBF network is put forward. Firstly, the initial PID parameters and their learning rates of controller are optimized using the improved polyclonal selection algorithm, which reduces the influence of control effect due to improper initial parameters. Secondly, the PID parameters of controller are adjusted on-line based on the RBF identification network during the liquid level control of water tank system. The simulation results show that the proposed controller is valid in the liquid level control of water tank system. Compared with other corresponding control algorithms, the proposed controller is characterized by quick response speed and small overshoot and error.

Keywords

adaptive control; learning systems; level control; neurocontrollers; optimisation; process control; radial basis function networks; tanks (containers); three-term control; water storage; 2-container water tank system; PID controller; RBF identification network; adaptive control; learning rates; liquid level control; polyclonal selection algorithm; process control; Adaptive control; Chemical industry; Containers; Control systems; Fuzzy control; Level control; Process control; Radial basis function networks; Sliding mode control; Three-term control; liquid level control; polyclonal selection algorithm; radial basis function network; water tank;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Technology (ICCET), 2010 2nd International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-6347-3

Type

conf

DOI

10.1109/ICCET.2010.5485592

Filename

5485592