Control of coagulation process by dual wavelength article analyzer

1997 ◽  
Vol 36 (4) ◽  
pp. 135-142 ◽  
Author(s):  
Norihito Tambo ◽  
Yoshihiko Matsui ◽  
Ken-ichi Kurotani ◽  
Masakazu Kubota ◽  
Hirohide Akiyama ◽  
...  
Keyword(s):  
Water Quality ◽  
Control System ◽  
Predictive Control ◽  
Control Method ◽  
Feedforward Control ◽  
Raw Water ◽  
Floc Size ◽  
Coagulation Process ◽  
Series Of Experiments ◽  
Size Data

A coagulation process for water purification plants mainly uses feedforward control based on raw water quality and empirical data and requires operator's help. We developed a new floc sensor for measuring floc size in a flush mixer to be used for floc control. A control system using model predictive control was developed on the floc size data. A series of experiments was performed to confirm controllability of settled water quality by controlling flush mixer floc size. An automatic control with feedback from the coagulation process was evaluated as practical and reliable. Finally this new control method was applied for actual plant and evaluated as practical.

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.

scholarly journals Self-Triggered Model Predictive Control for Linear Systems Based on Transmission of Control Input Sequences

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Koichi Kobayashi
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Linear Systems ◽  
Communication Networks ◽  
Predictive Control ◽  
Control Method ◽  
Input Sequence ◽  
Networked Control System ◽  
Control Input ◽  
Sampled Data

A networked control system (NCS) is a control system where components such as plants and controllers are connected through communication networks. Self-triggered control is well known as one of the control methods in NCSs and is a control method that for sampled-data control systems both the control input and the aperiodic sampling interval (i.e., the transmission interval) are computed simultaneously. In this paper, a self-triggered model predictive control (MPC) method for discrete-time linear systems with disturbances is proposed. In the conventional MPC method, the first one of the control input sequence obtained by solving the finite-time optimal control problem is sent and applied to the plant. In the proposed method, the first some elements of the control input sequence obtained are sent to the plant, and each element is sequentially applied to the plant. The number of elements is decided according to the effect of disturbances. In other words, transmission intervals can be controlled. Finally, the effectiveness of the proposed method is shown by numerical simulations.

Design of a strip thickness control system for tandem cold mills using H∞ control techniques

2003 ◽  
Vol 217 (4) ◽  
pp. 319-327
Author(s):  
S S Kim ◽  
J S Kim ◽  
S Y Yang ◽  
B R Lee ◽  
K K Ahn
Keyword(s):  
Control System ◽  
High Performance ◽  
Control Method ◽  
Feedforward Control ◽  
Thickness Variation ◽  
Linear Quadratic ◽  
Design Procedures ◽  
Control Techniques ◽  
Multivariable Control Systems ◽  
Control Units

In order to meet the requirement for higher thickness accuracy in cold-rolling mill processes, it is strongly desired to have an increasing high performance in control units. To meet this requirement, an output regulating control system with a roll-eccentricity estimator for each rolling stand of tandem cold mills was considered. Assuming entry thickness variation as well as roll eccentricity to be the major disturbances, a synthesis of multivariable control systems is presented and based on H∞ control theory, which can reflect knowledge of the input direction and spectrum of disturbance signals on design. Then, to reject roll eccentricity effectively, a weight function having some poles on the imaginary axis is introduced. This leads to a non-standard H∞ control problem, and the design procedures for solving this problem are analytically presented. The effectiveness of the proposed control method is evaluated through computer simulations and compared with the conventional linear quadratic control and feedforward control methods for roll eccentricity.

A Study of Predictive Control of Energy-Saving of Heating Process

2011 ◽  
Vol 328-330 ◽  
pp. 1810-1813
Author(s):  
Xue Li Zhu ◽  
Shu Xian Zhu ◽  
Sheng Hui Guo
Keyword(s):  
Control System ◽  
Error Correction ◽  
Energy Saving ◽  
Real Time ◽  
Predictive Control ◽  
Control Method ◽  
Heating System ◽  
Heating Power ◽  
Heating Process ◽  
Power Station

This paper presents a predictive control method of heating system of heating power station. Firstly, the forecast of heating load is introduced using time series analysis, and the obtained result is used as an energy-saving initial value of predictive control system. Secondly, model simplification method is given and immediate control law is derived, the predictive model order is decreased from N to n. Simplification model satisfies the demand of real-time property of the control system. Thirdly, predictive error correction is used to replace error correction to implement the correction of optimum control of the system, which can improve adaptability and robustness of the system. Finally, simulation of heating system of heating power station is conducted and the results prove that the algorithm is effective in ensuring real-time control, improving tracking and robustness property.

The Research on Intelligent Control Method for EHP System

2012 ◽  
Vol 580 ◽  
pp. 12-15 ◽  
Author(s):  
Yi Wan ◽  
Qi Bo Cai ◽  
Huan Wang
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Intelligent Control ◽  
Internal Model ◽  
High Speed ◽  
Control Method ◽  
Internal Model Control ◽  
Support Vector ◽  
Proportional Control ◽  
Self Adaptive

Optimized machine learning algorithm is applied to control modeling of high-speed electric-hydraulic proportional system of high nonlinear in this paper, a identification model of high-speed electric-hydraulic proportional system is built based on support vector machines, fusion intelligent method of dynamic self-adaptive internal model control and predictive control is realized for high-speed electric-hydraulic proportional control system. Internal model and inverse controller model are online adjusted together. Simulation shows the satisfactory tracking effect by intelligent technology of dynamic self-adaptive internal control and predictive control based on the support vector machine, the dynamic characteristic is greatly improved by the intelligent control strategy for high-speed electric-hydraulic proportional control system, good tracking and control effect is reached in condition of high frequency response. It provides a new intelligent control method for high-speed electric-hydraulic proportional system.

The Design and Implementation of Fuzzy Neural Network Control Algorithms in Urban Sewage Treatment Control System

2011 ◽  
Vol 230-232 ◽  
pp. 1133-1140
Author(s):  
Zhao Hui Shi
Keyword(s):  
Water Quality ◽  
Control System ◽  
Fuzzy Control ◽  
Automatic Control ◽  
Treatment Process ◽  
Control Method ◽  
Sewage Treatment ◽  
Network Control ◽  
Object Oriented Programming ◽  
Control Software

In this paper,the artificial intelligence control technology is used in sewage treatment plants, we use fuzzy control method in the sewage treatment process, we use the dynamic fuzzy control in the water quality of the sewage treatment process parameters , on this basis, we completed the automatic control system software design, the upper control software we use the WinCC configuration ,the next bit control softwarewe use the STEP7 5.1. We use the object-oriented programming idea to improve the efficiency of automatic control software. We developed the application communication protocol between the upper and lower computer layer, the next crew and the host computer can run independently when they are not connected,when the communication connects again, you can pass the parameters of the system from each other to avoid the loss of valid data. The central control system monitors the plant process and equipment operation all the time, the remote control substitutes for the original analog console, it is important simulation parameters to trend display, allowing the operator to better control water quality.

Modified Predictive Control System of the DC-DC Boost Converter

2021 ◽  
Vol 26 (6) ◽  
pp. 533-546
Author(s):  
A.A. Cherdintsev ◽  
◽  
A.V. Shagin ◽  
S.A. Lupin ◽  
◽  
...  
Keyword(s):  
Control System ◽  
Objective Function ◽  
Predictive Control ◽  
Control Method ◽  
Reference Level ◽  
Computing Power ◽  
Fast Transient Response ◽  
Prediction Horizon ◽  
The Cost ◽  
High Degree

Nowadays, predictive control systems are becoming more and more popular, which significantly reduce the cost of setting up converters. However, DC-DC converter control problem persists. In this work, a modified model of the predictive control system (MPCS) for step-up DC-DC converters is presented. For its implementation, a nonlinear model of a converter with discrete time switching was derived, which describe a continuous conduction mode of operation. The synthesis of the controller was achieved by formulating the objective function that should be minimized considering the dynamic model of the converter. The proposed predictive control strategy, used as a voltage control system, allows keeping the output voltage at the reference level. The modified system for calculating the objective function makes it possible to significantly reduce the required computing power and expand the prediction horizon. The results of modeling have been presented that demonstrate the advantages of the proposed control method: a fast transient response and a high degree of robustness.

Design of the Intelligent Control System Integration of Wastewater Treatment

2014 ◽  
Vol 716-717 ◽  
pp. 1591-1594
Author(s):  
Wen Hua Chen ◽  
Qiang Cai ◽  
Xu Wang
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Control System ◽  
Intelligent Control ◽  
High Efficiency ◽  
Control Method ◽  
Reference Value ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Intelligent Control System

In order to achieve the integrated process of wastewater treatment, this research designs a kind of intelligent control system that can monitoring water quality parameters in real-time, which is small, convenient control, high efficiency and low consumption. The acquisition station and control station of the system are based on STM32F107 and industrial control tablet, combined with IASBR process to achieve simultaneous removal of organic matter, nitrogen, phosphorus and COD in wastewater. This system can monitor water temperature, pH, ORP, DO and other water quality parameters. Aiming at the uncertainty of the DO in process control, the fuzzy control method is proposed to realize the rationalization of aeration, meet the needs of wastewater biochemical treatment of the DO. It has a certain reference value to the intelligent development of integrated wastewater treatment.

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