ADAPTIVE SYSTEM OF FUZZY-LOGICAL REGULATION BY THE TEMPERATURE MODE OF THE DRUM BOILER

Authors

  • Dilnoza Umurzakova Maxamadjonovna
  • Isamiddin Siddikov
  • Isamiddin Siddikov
  • Hurshida Bakhrieva

DOI:

https://doi.org/10.31436/iiumej.v21i1.1220

Keywords:

fuzzy model, PID-controller, neural networks, drum boiler, controller, adaptive system, temperature, heat power industry.

Abstract

 The article discusses the creation of an adaptive system for managing dynamic objects based on neuro-fuzzy technology. This technology is used to actively identify and create temperature control algorithms for the superheated steam of a drum boiler in the presence of disturbances associated with a change in load. To solve this problem, the use of a fuzzy-logical controller is proposed. The rule base of this regulator is defined. A technique is proposed for determining the optimal number of neurons and the number of hidden layers. The neuro-fuzzy model of the controller is presented in the form of a multilayer neural network without feedback, which is characterized by a simple implementation in practice. The use of a fuzzy-logical controller gives the automatic control system the ability to maintain technological parameters at a given level in the presence of external disturbing influences, and also makes it possible to efficiently control the process.

ABSTRAK: Artikel ini membincangkan rekaan sistem penyesuaian bagi mengurus objek dinamik berdasarkan teknologi neura-kabur. Teknologi ini digunakan bagi mengenal pasti secara aktif dan mencipta algoritma kawalan suhu bagi stim melampau panas dalam drum dandang dengan kehadiran gangguan berkaitan perubahan beban. Bagi menyelesaikan masalah ini, penggunaan pengawal logik-kabur telah dicadangkan. Asas peraturan bagi pengaturan ini ditentukan. Satu teknik dicadangkan bagi mendapat bilangan optima neuron dan bilangan lapisan tersembunyi. Model neura-kabur pengawal ini dikemukakan dalam bentuk rangkaian neural berlapis tanpa suap balik, bercirikan praktik pelaksanaan mudah. Penggunaan pengawal logik-kabur memberi sistem kawalan automatik kebolehan mengekalkan parameter teknologi pada tahap tertentu dengan kehadiran pengaruh gangguan luar, dan juga memberi kebolehan proses kawalan yang cekap.

 

Downloads

Download data is not yet available.

References

O’Dwyer A. (2009) Handbook of PI and PID Controller Tuning Rules. 3rd Edition. Dublin: Institute of Technology; Ireland, Imperial College Press. 529 p.

Astrom KJ. (2006) Advanced PID control/ K. J. Astrom, T. Hagglund – ISA (The instrumentation, Systems, and Automation Society), - 460 p.

Demchenko VA. (2001) Automation and modeling of technological processes at nuclear power plants and thermal power plants / V. A. Demchenko. - Odessa: Astroprint. - 308 p.

Kim T, Maruta I, Sugie T. (2008) Robust PID controller tuning based on the constrained particle swarm optimization, Automatica, 44(4): 1104-1110.

Lu C, Hsu C, Juang C. (2013) Coordinated control of flexible AC transmission system devices using an evolutionary fuzzy lead-lag controller with advanced continuous ant colony optimization, IEEE Transactions on Power Systems, 28(1): 385-392.

Pelusi D. (2012) PID and intelligent controllers for optimal timing performances of industrial actuators, International Journal of Simulation: Systems, Science and Technology, 13(2): 65-71.

Pelusi D, Mascella R. (2013) Optimal control algorithms for second order systems, Journal of Computer Science, 9(2): 183-197.

Pletnev GP. (2007) Automation of Technological Processes and Productions in Heatand-Power Engineering. 4th Edition. Moscow: Publishing House Moscow Power Engineering Institute. -352 p.

Rotach VY. (2008) The Theory of Automatic Control. Moscow: Publishing House Moscow Power Engineering Institute. - 396 p.

Siddikov IX, Iskandarov Z. (2018) Synthesis of adaptive-fuzzy control system of dynamic in conditions of uncertainty of information // International Journal of Advanced Research in Science, Engineering and Technology, 5(1): 5089-5093.

Siddikov IX, Umurzakova DM. (2019) Features of automatic control of technological parameters of water level in the drum steam boilers, Journal of Southwest Jiaotong University, 54(3): 1-10. DOI: 10.35741/issn.0258-2724.54.3.1.

Siddikov IX, Umurzakova DM. (2019) Mathematical Modeling of Transient Processes of the Automatic Control System of Water Level in the Steam Generator, Universal Journal of Mechanical Engineering, 7(4): 139-146. DOI: 10.13189/ujme.2019.070401.

Sidikov IX, Umurzakova DM. (2019) Adaptive neuro-fuzzy regulating system of the temperature mode of the drum boiler // International Journal of Advanced Research in Science, Engineering and Technology, 6(1): 7869-7872.

Soroko EM, Golden Sections. (2006) Processes of Self-Organizing and Evolution in Systems: Introduction into the General Theory of System Harmonizing. Moscow: KomKniga. -264 p.

Downloads

Published

2020-01-20

How to Cite

Umurzakova, D., Siddikov, I., Siddikov, I., & Bakhrieva, H. (2020). ADAPTIVE SYSTEM OF FUZZY-LOGICAL REGULATION BY THE TEMPERATURE MODE OF THE DRUM BOILER. IIUM Engineering Journal, 21(1), 182 - 192. https://doi.org/10.31436/iiumej.v21i1.1220

Issue

Section

Engineering Mathematics and Applied Science