Process Control of Dense Medium Separation Based on Improved Implicit Generalized Predictive Control Algorithm

2014 ◽  
Vol 11 (16) ◽  
pp. 5957-5968
Author(s):  
Zhenguan Cao
Keyword(s):  
Process Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Dense Medium ◽  
Generalized Predictive Control

Multi-Rate Generalized Predictive Control for Multi-Variable Systems

1993 ◽  
Vol 207 (4) ◽  
pp. 253-260
Author(s):  
I O Park ◽  
J H Oh
Keyword(s):  
Process Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Model Identification ◽  
Measurement Noise ◽  
Noise Model ◽  
Generalized Predictive Control ◽  
Identification Algorithm ◽  
Stochastic Framework ◽  
And Control

The purpose of this paper is to drive the adaptive multi-rate generalized predictive control for multi-variable systems in a stochastic framework. Modelling disturbances as white noise is inadequate for process control because most disturbances encountered in process control are coloured or non-stationary in nature. For that reason a stochastic parallel model identification algorithm for a multi-rate-sampled system is proposed. No attempt is made to identify the noise model. Hence the algorithm is applicable to any measurement noise case. The measurement noise can be arbitrary (for example coloured or non-stationary noise), except for the assumption that it and control inputs are stochastically uncorrelated. Then the control algorithm based on the generalized predictive control is proposed. In order to demonstrate the effectiveness of the proposed control algorithm a simulation study is carried out. The closed-loop performances are excellent.

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.

On a generalized predictive control algorithm

1987 ◽  
Vol 9 (5) ◽  
pp. 369-377 ◽  
Author(s):  
R Gorez ◽  
V Wertz ◽  
Zhu Kuan-Yi
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Generalized Predictive Control

A Nonlinear System Research Based on PID General Algorithm Control

2013 ◽  
Vol 740 ◽  
pp. 51-55
Author(s):  
Yu Bao Hou ◽  
Shu Yan Tang
Keyword(s):  
Nonlinear System ◽  
Control Systems ◽  
Predictive Control ◽  
Control Algorithm ◽  
General Algorithm ◽  
Generalized Predictive Control ◽  
System Research ◽  
Control Quality

Generalized predictive control (GPC) algorithm has been applied to all kinds of industry control systems. But systemic and effective method for nonlinear system has not been found.To this problem,this paper integrates the characteristics of PID technology and GPC,present a PID generalized predicitive control algorithm for a class of nonlinear system,and improves the control quality of the system.

Study on Control of the Second Carbonation in the Clarifying Process of Sugar Cane Juice via Generalized Predictive Control Algorithm

2013 ◽  
Vol 303-306 ◽  
pp. 1257-1260 ◽  
Author(s):  
Chun Ning Song ◽  
Wen Han Zhong
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Bp Neural Network ◽  
Sugar Cane ◽  
Control Algorithm ◽  
Generalized Predictive Control ◽  
Cane Juice ◽  
Sugar Cane Juice ◽  
High Control ◽  
Complex Nonlinear Systems

The second carbonation in the clarifying process of sugar cane juice is a dynamic nonlinear system which has the characteristics of strong non-linearity, multi-constraint, large time-delay, multi-input and other characteristics of complex nonlinear systems. In this paper, BP neural network is applied to the model of the second carbonation clarifying process of sugar cane juice. The generalized predictive control algorithm is employed to the optional control of color value in clarifying process of second carbonation. The result of Matlab simulation shows that generalized predictive control algorithm based on BP neural network implement the optimal control of the second carbonation with strong robustness and high control precision.

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