A fuzzy logic intelligent control system architecture for an autonomous leader-following vehicle

1997 ◽  
Author(s):  
K.C. Choek ◽  
G.E. Smid ◽  
K. Koayashi ◽  
J.L. Overholt ◽  
P. Lescos
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Intelligent Control ◽  
System Architecture ◽  
Intelligent Control System ◽  
Leader Following ◽  
Control System Architecture

scholarly journals Intelligent Control System Architecture for Phosphorus Production from Apatite-Nepheline Ore Waste

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6469
Author(s):  
Maksim Dli ◽  
Andrey Puchkov ◽  
Artem Vasiliev ◽  
Elena Kirillova ◽  
Yuri Selyavskiy ◽  
...  
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
System Architecture ◽  
Simulation Models ◽  
Information Support ◽  
Software Environment ◽  
Intelligent Control System ◽  
Phosphorus Production ◽  
And Control ◽  
Control System Architecture

This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat and polymodal information, and control goals differ at different levels not only in effectiveness criteria, but also in the structuredness of the level problems. On this basis, it is proposed that intelligent methods be used for the implementation of information processes and control goals at individual levels and the whole system. The artificial intelligence methods underlying the informational model of a control system offer solutions to problems of analyzing control processes at different hierarchy levels, namely the initial level of sensing devices, the levels of programmable logic controllers, dispatching of control and production processes, enterprise management and strategic planning. Besides, the intelligent control system architecture includes analytical and simulation models of processes occurring in the multistage procedure of ore waste processing by a plant consisting of a granulating machine, a conveyor-type multichambercalcining machine, and an ore thermal furnace. The architecture of information support for the control system comprises a knowledge-based inference block intended for implementing the self-refinement of neural network and simulation models. Fuzzy logic methods are proposed for constructing this block. The paper considers the deployment of control algorithms for a phosphorus production system using the Matlab software environment on the basis of a modern complex system development paradigm known as the model-oriented design concept.

A fuzzy logic intelligent control system paradigm for an in-line-of-sight leader-following HMMWV

1997 ◽  
Vol 14 (6) ◽  
pp. 407-420 ◽  
Author(s):  
Ka C. Cheok ◽  
Gert-Edzko Smid ◽  
Kazuyuki Kobayashi ◽  
James L. Overholt ◽  
Paul Lescoe
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Intelligent Control ◽  
Line Of Sight ◽  
Intelligent Control System ◽  
Leader Following ◽  
System Paradigm

scholarly journals Control System Architecture for a Cement Mill Based on Fuzzy Logic

2015 ◽  
Vol 10 (2) ◽  
pp. 165 ◽  
Author(s):  
Claudiu Raul Costea ◽  
Helga Maria Silaghi ◽  
Doina Zmaranda ◽  
Marius Alexandru Silaghi
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
System Architecture ◽  
Control System Architecture

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

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