Application of GPC Algorithm in Level Control System

2014 ◽  
Vol 541-542 ◽  
pp. 1222-1227 ◽  
Author(s):  
Yan Xiang Wu ◽  
Zhong Yong Gao
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Control Device ◽  
Generalized Predictive Control ◽  
Water Tank ◽  
Level Control ◽  
Control Effect ◽  
Response Performance ◽  
Set Up ◽  
Improved Methods

In order to improve the dependability and security of the lever control system, we introduced the generalized predictive control (GPC) algorithm. We used MATLAB/Simulink program development tools to control the double capacity water tank. At first, we used the water tank level control device as the object and set up a mathematical model of the control system. Then we put forward the generalized predictive control algorithm based on the model. The simulation results show that the presented algorithm has a good dynamic response performance, fast-track settings, and a preferable control effect. Experimental results show that the improved methods are reasonable and practicable.

Parameter Setting Based on JGPC Algorithm for Liquid Level Control System

2014 ◽  
Vol 513-517 ◽  
pp. 3094-3098
Author(s):  
Yan Xiang Wu ◽  
Zhong Yong Gao
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Control Device ◽  
Generalized Predictive Control ◽  
Water Tank ◽  
Parameter Setting ◽  
Level Control ◽  
Control Effect ◽  
Level Control System ◽  
Set Up

Double-tank water level control system is a nonlinear system in ship. It has long cubage delay and bad anti-jamming ability in ordinary. In order to improve the dependability and security of the lever control system, a improved generalized predictive control (JGPC) algorithm was introduced. We set up a mathematical model of control system with the water tank level control device as the object. Based on the mode, the improved generalized predictive control algorithm was put forward and introduced the parameter setting of JGPC algorithm. The simulation results show that the presented algorithm has a good dynamic response performance, fast-track settings, and a preferable control effect. Experimental results show that the improved methods are reasonable and practicable.

The Research of Air Precooling System Based on Generalize Predictive Control Strategy

2013 ◽  
Vol 433-435 ◽  
pp. 1091-1098
Author(s):  
Wei Bo Yu ◽  
Cui Yuan Feng ◽  
Ting Ting Yang ◽  
Hong Jun Li
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Control Algorithm ◽  
Exchange Process ◽  
Generalized Predictive Control ◽  
Matlab Simulation ◽  
Control Effect ◽  
Heat Exchange Process ◽  
Complex Control System ◽  
And Control

The air precooling system heat exchange process is a complex control system with features such as: nonlinear, lag and random interference. So choose Generalized Predictive Control Algorithm that has low model dependence, good robustness and control effect, as well as easy to implement. But due to the large amount of calculation of traditional generalized predictive control and can't juggle quickness and overshoot problem, an improved generalized predictive control algorithm is proposed, then carry out the MATLAB simulation, the experimental results show that the algorithm can not only greatly reduce the amount of computation, but also can restrain the overshoot and its rapidity.

scholarly journals RESEARCH OF LIQUID LEVEL CONTROL SYSTEM / SKYSČIO LYGIO VALDYMO SISTEMOS TYRIMAS

2015 ◽  
Vol 7 (3) ◽  
pp. 317-322
Author(s):  
Dominykas Beištaras
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Liquid Level ◽  
Water Tank ◽  
Level Control ◽  
Level Control System ◽  
Filling Time ◽  
Control System Model ◽  
Liquid Level Control

This paper presents liquid level control system model and analysis of dynamic characteristics. The system consists of scalar controlled induction motor drive, fuzzy logic controller, water tank and centrifugal pump. Simulink models of water tank, pump and controller are presented. The simulation of the system shows that the use of fuzzy logic controller reduces valve opening time and reservoir filling time. Nagrinėjamas skysčio lygio valdymo sistemos imitacinių modelių sudarymas, analizuojamos dinaminės charakteristikos. Valdymo sistema sudaryta iš skaliariniu būdu valdomos dažninės elektros pavaros su neraiškiosios logikos reguliatoriumi, vandens rezervuaro ir išcentrinio siurblio. Sudaryti rezervuaro, siurblio ir reguliatoriaus Simulink modeliai. Atlikus imitacijas gauta nedimensinė siurblio charakteristika, apibūdinanti siurblio veikimą, esant bet kokiam sukimosi greičiui. Nustatyta, kad sistemoje su neraiškiosios logikos reguliatoriumi vožtuvas yra atidaromas greičiau nei sistemoje su proporcinguoju integraliniu (PI) reguliatoriumi, ir todėl sumažinama rezervuaro pripildymo trukmė.

Hot Blast Stove Temperature Control System Based on Neural Network Predictive Control

2014 ◽  
Vol 709 ◽  
pp. 281-284 ◽  
Author(s):  
Yao Wu Tang ◽  
Xiang Liu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Predictive Control ◽  
Control Method ◽  
Delay System ◽  
Temperature Control System ◽  
Control Effect ◽  
Rolling Optimization ◽  
Hot Blast ◽  
Neural Network Predictive Control

Chain type coal-fired hot blast furnace boiler has a strong coupling, large delay, large inertia characteristics. Control effect of control method of mathematic modeling method and the classical routine of it is very difficult to produce the ideal. The predictive control theory combined with neural network theory. Through the model correction and rolling optimization control method of the system is good to overcome the effects of model error and time-varying process. The experimental results showed that neural network predictive control system is improved effectively the static precision and dynamic characteristic. It has better practicability of boiler temperature of this kind of large time delay system.

Performance-Adaptive Generalized Predictive Control-Based Proportional-Integral-Derivative Control System and Its Application

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Takao Sato ◽  
Toru Yamamoto ◽  
Nozomu Araki ◽  
Yasuo Konishi
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Pid Control ◽  
Design Method ◽  
Design Parameters ◽  
Generalized Predictive Control ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Proportional Integral Derivative Control

In the present paper, we discuss a new design method for a proportional-integral-derivative (PID) control system using a model predictive approach. The PID compensator is designed based on generalized predictive control (GPC). The PID parameters are adaptively updated such that the control performance is improved because the design parameters of GPC are selected automatically in order to attain a user-specified control performance. In the proposed scheme, the estimated plant parameters are updated only when the prediction error increases. Therefore, the control system is not updated frequently. The control system is updated only when the control performance is sufficiently improved. The effectiveness of the proposed method is demonstrated numerically. Finally, the proposed method is applied to a weigh feeder, and experimental results are presented.

The Research and Design of Liquid Level Control System Based on Computer Nerve Network

2012 ◽  
Vol 591-593 ◽  
pp. 1629-1632
Author(s):  
Li Zhang ◽  
Jian Hui Wang ◽  
Hou Yao Zhu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Pid Control ◽  
Liquid Level ◽  
Level Control ◽  
Control Effect ◽  
Nerve Network ◽  
Level Control System ◽  
Pid Neural Network ◽  
Liquid Level Control

This thesis mainly elaborated the PID neural network feed-forward algo-rithm and back propagation algorithm and the structure form of its controller, then make use of MATLAB to simulate the liquid level adjusting system, analysis its control perform-ance and choose appropriate neural network parameters, and compared with the traditional PID control effect, analyzes the advantages of PID neural network. Through the comparison with the conventional PID control, PID neural network is superior to the traditional PID. The traditional PID control tuning parameters has a large number of thumb rules for reference, but the setting out of the parameters is not necessarily good. And sometimes we have to modify the parameters if we wound the better control effect. PID neural network is set up as long as the learning step in accordance with the PID rule set. this paper has show that Liquid Level Control System based on Computer Nerve Network has good control effect of rapid and effective.

Control Strategy Study on Drum Water Level of Supercharged Boiler Based on Radiation Energy Signal

2011 ◽  
Vol 328-330 ◽  
pp. 1872-1875
Author(s):  
Guo Yi Zhou ◽  
Wen Sheng He ◽  
Huai Chun Zhou
Keyword(s):  
Control System ◽  
Water Level ◽  
Control Strategy ◽  
Radiation Energy ◽  
Feed Water ◽  
Level Control ◽  
Strategy Study ◽  
Level Control System ◽  
Set Up ◽  
Energy Signal

The deficiencies of drum water level control system and unstable combustion of supercharged boiler could result some serious accident such as water level fluctuating greatly, pipes in furnace overheating and bursting, boiler loss water. In order to solve the problems, flame detect system was used to get flame images of boiler's furnace, and radiation energy signal was introduced into drum water level control system to add one auxiliary control loop of combustion side. The new control strategy was established and simulation model was set up. The simulation results show that the new control system could adjust feed water within 20s, and eliminated the disturbance of water level within 60s by way of monitoring radiation energy signal, the fluctuating range was also decreased significantly.

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