Title :
Liquid level control of water tank system based on improved polyclonal selection algorithm and RBF network
Author_Institution :
Fac. of Mech. Eng., Huaiyin Inst. of Technol. Huaian, Huaiyin, China
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;
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
DOI :
10.1109/ICCET.2010.5485592
