Application of Multi-Mode Intelligent Control System in Grate Cooler Optimization

2014 ◽  
Vol 536-537 ◽  
pp. 1137-1142
Author(s):  
Xiao Ming Li ◽  
Xiao Hong Wang ◽  
Hong Liang Yu
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
Control Method ◽  
Linear Time ◽  
Good Control ◽  
Control Effect ◽  
Expert Control ◽  
Intelligent Control System ◽  
Grate Cooler ◽  
Multi Mode

According to the characteristics of non-linear, time-varying and large time delay in the control of grate cooler, a multi-mode intelligent control method is proposed in the paper.The multi-mode intelligent controller is builded up by variable integral PID control, fuzzy control, Bang-Bang control and expert control. This control method through a multi-mode intelligent control rules automatically identifies different modal and chooses a corresponding control algorithm to correct variable integral PID control.Industrial applications show that the control system has good robustness, achieved good control effect.

Intelligent Operation Control for the Fused Magnesia Production

2011 ◽  
Vol 391-392 ◽  
pp. 1450-1454
Author(s):  
Yong Jian Wu ◽  
Ping Zhou ◽  
Pin Shang ◽  
Tian You Chai
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
Control Strategy ◽  
Control Method ◽  
Level Control ◽  
Loop Control ◽  
Intelligent Control System ◽  
Technical Requirements ◽  
Operation Control ◽  
Lower Loop

An electro-fused magnesia furnace (EFMF) is used to produce electro-fused magnesia. Due to the complex dynamic characteristics of the EFMF production process, it is difficult to achieve the satisfactory control performances only by the independent conventional control method. As a result, the lower loop control with manual operations is still widely used in practice. However, the manual operation cannot ensure that the actual production qualities and the energy consumption of unit production meet the technical requirements all the time. In this paper, an intelligent operation control strategy is developed for the EFMF to automatically adjust the setpoints of the lower level control system. Based on the proposed intelligent control strategy, an intelligent control system for the EFMF is built and implemented on site. Industrial application has demonstrated that the intelligent control system can achieve reliable, accurate and timely control performances.

Implementation of Intelligent Control System for Autonomous Underwater Vehicle

2014 ◽  
Vol 701-702 ◽  
pp. 704-710 ◽  
Author(s):  
Viacheslav Pshikhopov ◽  
Yuriy Chernukhin ◽  
Viktor Guzik ◽  
Mikhail Medvedev ◽  
Boris Gurenko ◽  
...  
Keyword(s):  
Control System ◽  
Motion Control ◽  
Intelligent Control ◽  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Underwater Vehicle ◽  
Intelligent Control System ◽  
Azov Sea ◽  
Complex Simulation ◽  
Point To Point

This paper introduces the implementation of intelligent motion control and planning for autonomous underwater vehicle (AUV). Previously developed control system features intelligent motion control and planning subsystem, based on artificial neural networks. It allows detecting and avoiding moving obstacles in front of the AUV. The motion control subsystem uses position-trajectory control method to position AUV, move from point to point and along given path with given speed. Control system was tested in the multi-module simulation complex. Simulation showed good results – AUV successfully achieved given goals avoiding collisions not only with static obstacles, but also with mobile ones. That allows using the proposed control system for the groups of vehicles. Besides simulation, control system was implemented in hardware. AUV prototype passed tests in Azov Sea and proved its efficiency.

Using DCS to Realize Ball Mill Fuzzy Control System

2014 ◽  
Vol 568-570 ◽  
pp. 1131-1134
Author(s):  
Yan Jun Wang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Ball Mill ◽  
Control Method ◽  
Good Control ◽  
Pi Controller ◽  
Decoupling Control ◽  
Control Effect ◽  
Hot Air ◽  
Look Up Table

By way of summarizes operation experience, using fuzzy control method to realize the decoupling control of coal mill cold air damper, hot air damper and coal feeder, by using cascade control of fuzzy control look up table and PI controller in DCS, it’s convenient to realized the automatic control of ball mill. Practice proves that this method is easy to achieve and good control effect could be achieved.

PLC-Based Embedded Intelligent Control Research

2015 ◽  
Vol 799-800 ◽  
pp. 1127-1131
Author(s):  
Wen Chong Cui ◽  
Yu Lin Dong
Keyword(s):  
Intelligent Control ◽  
Control Strategy ◽  
Control Method ◽  
Control Strategies ◽  
Rapid Development ◽  
Control Effect ◽  
Industrial Control ◽  
Expert Control ◽  
Control Research ◽  
Traditional Process

With the rapid development of industrialization, the intelligent control has increasingly replaced the traditional process control in PLC in recent years, in which some intelligent control strategy has been applied to industrial control cases, such as genetic algorithm, fuzzy control, expert control and neural network and so on. However, it is not sufficient to achieve the desired control effect if only an intelligent control method is applied in the intelligent control. Therefore, integrated intelligent control of various control strategies is bound to be a focus in the embedded intelligent control. At the same time, with growing power of the PLC processing, it is possible for complex algorithms to be used in the embedded application, which has great significance in the development of industrialization as well as intelligent control.

scholarly journals RANCANG BANGUN FERMENTOR YOGURT DENGAN SISTEM KONTROL LOGIKA FUZZY MENGGUNAKAN MIKROKONTROLER ATMEGA32 (Yogurt Fermenter Design with Fuzzy Logic Control System Using Microcontroller ATMega32)

2015 ◽  
Vol 34 (04) ◽  
pp. 456
Author(s):  
Dimas Firmanda Al Riza ◽  
Retno Damayanti ◽  
Yusuf Hendrawan
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Temperature Control ◽  
Intelligent Control ◽  
Fuzzy Logic Control ◽  
Fermentation Process ◽  
Linear Time ◽  
Intelligent Control System ◽  
Logic Control ◽  
System Method

Yogurt is milk fermented product that becomes popular recently. In yogurt processing, fermenter is the main device. Lactobacillus sp. and Streptococcus sp. are two probiotic bacteria species that are common to be used in yogurt fermentation process. Both bacteria grow well in a specific range of temperature between 40-45 C, so temperature control in fermenter operational becomes one of the important things to ensure speed and quality of fermentation process. Fermentation process is a process with high degree of uncertainty and categorized as non-linear time invariant system. Thus, classical control system method is difficult to be implemented. To overcome this issue, intelligent control system can be implemented to yogurt’s fermenter temperature control. One of intelligent control system method that can be implemented is fuzzy logic-based control system. In this study, fuzzy control system has been designed andimplemented for fermenter temperature control. Control system algorithm is integrated in ATMega16 (for On-Off logic control) and ATMega32 (for Fuzzy Logic control) microcontrollers. Experimental results of fermenter control system shows that temperature profile of fermenter with fuzzy logic control system is more stable by settling time around an hour and 15 minutes and error average of -0.36 oC. Fermentation process for 16 hours with fuzzy logic controller produce yogurt with pH value of 3.66, total number of Lactobacillus sp. is 4.85 x 10 cfu/mL and Streptococcus sp. is1.34 x 106 cfu/mL.Keywords: Fermentation, yogurt, cow milk, fuzzy, temperature control ABSTRAKYogurt merupakan produk olahan susu terfermentasi yang akhir-akhir ini mulai banyak disukai oleh masyarakat. Pada pengolahan susu menjadi yogurt, fermentor digunakan sebagai alat utama. Lactobacillus sp. dan Streptococcus sp. merupakan dua spesies bakteri yang biasa digunakan dalam proses fermentasi yogurt. Kedua jenis bakteri ini tumbuhdengan baik pada suhu yang spesifik yaitu antara 40–45 C, sehingga pengendalian suhu pada operasi fermentor merupakan hal yang penting agar proses fermentasi dapat berjalan secara cepat dan baik. Proses fermentasi merupakan proses yang memiliki tingkat ketidakpastian yang tinggi dan merupakan sistem non-linear time variant, sehinggadesain sistem kontrol klasik akan sulit untuk diterapkan. Untuk mengatasi hal ini sistem kontrol cerdas dapat untuk diimplementasikan pada pengendalian suhu fermentor yogurt. Salah satu dari metode sistem kontrol cerdas yang dapat digunakan adalah sistem kontrol dengan logika fuzzy. Pada penelitian ini telah dilakukan rancang bangun sistempengendalian suhu berbasis algoritma fuzzy pada fermentor yogurt. Algoritma sistem kendali diintegrasikan dalam mikrokontroler ATMega16 (untuk logika ON-OFF) dan ATMega32 (untuk logika fuzzy). Hasil uji sistem pengendalian suhu fermentor menunjukkan bahwa dengan menggunakan algoritma fuzzy sistem pengendalian lebih stabil dengansettling time selama 1 jam 20 menit dan rata-rata error sebesar -0,36 oC. Proses fermentasi selama 16 jam menggunakan fermentor dengan kontroler fuzzy menghasilkan yogurt dengan pH sebesar 3,66, jumlah mikroba Lactobacillus sp. sebanyak 4,85 x 108cfu/mL, dan Streptococcus sp. sebanyak 1,34 x 10 6 cfu/mL.Kata kunci: Fermentasi, yogurt, susu sapi, fuzzy, kontrol suhu

scholarly journals An Intelligent Control System of Remanufacturing Assembly for Improving Quality and Production Efficiency

2021 ◽  
Author(s):  
Conghu Liu ◽  
Wei Cai ◽  
Guang Zhu ◽  
Mengdi Gao
Keyword(s):  
Control System ◽  
Real Time ◽  
Intelligent Control ◽  
Production Efficiency ◽  
Control Method ◽  
Coupling Mechanism ◽  
Real Time Monitoring ◽  
Dynamic Compensation ◽  
Positive Role ◽  
Intelligent Control System

Abstract Remanufacturing has been considered to be one of the most effective ways to deal with sustainable manufacturing. The integration of intelligent technology and remanufacturing assembly system is a necessary way for the development of remanufacturing industry. This paper proposes an intelligent control system for improving the quality and production efficiency of the remanufacturing assembly (reassembly) systems. First, the state space model of reassembly is constructed and deduced to reveal the quality transfer and coupling mechanism of reassembly process. An optimization model of the reassembly scheme is established for minimizing the comprehensive cost. Then, an intelligent control system for reassembly process is proposed, which is a real-time monitoring and dynamic compensation response to address abnormal quality and to achieve intelligent control of reassembly process. The data model, information perception and fusion technology, real-time monitoring and dynamic compensation of reassembly quality are studied and implemented. Finally, the prototype intelligent control system of reassembly is developed, which illustrates its practicability offering a technical support for sustainability of remanufacturing. It can monitor the abnormal quality in real time and make dynamic compensation response, and realize the intelligent control of reassembly process. It plays a positive role in improving quality, reducing cost and enhancing customer satisfaction. This intelligent control method is more suitable for the reassembly system of complex machinery, especially under uncertain operating environment.

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.

Regulation of PID Controller Parameters Based on Ant Colony Optimization Algorithm in Bending Control System

2011 ◽  
Vol 128-129 ◽  
pp. 205-210 ◽  
Author(s):  
Yu Zhen Yu ◽  
Xin Yi Ren ◽  
Chun Yan Deng ◽  
Jing Jing Yu ◽  
Shu Zhen Li ◽  
...  
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Ant Colony Algorithm ◽  
Control Method ◽  
External Disturbance ◽  
Good Control ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Control Effect ◽  
Dynamic Quality

The bending-roll control system has characteristics of time-varying, time-delay, nonlinearity and serious external disturbance, so it is hard to establish precise math model that be applied to control. In view of the problems above, ant colony algorithm is used to tuning parameters of PID controller and concrete step of PID parameters tuning based on ant colony algorithm is given. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in bending control system that proved the correctness and effectiveness of the control method.

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