Modeling and control of boiler in thermal power plant using model reference adaptive control
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.1.27Keywords:
Boiler, Model Reference Adaptive Control, Modeling, Multi input Multi Output, SimulationDimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The boiler is a multi-variable system, which is very difficult to control due to its nonlinear behavior, uncertainties, interactions between variables, and unmeasured and frequent disturbances. Instead of conventional control techniques, modern control techniques are being implemented in most boilers by industries. Mathematical modeling is a useful tool to analyze a complex system’s performance and design a controller for the same. The mathematical model is derived from the open-loop data obtained from the process station. The mathematical equation is then derived using the decoupling technique in terms of transfer function. An adaptive controller is designed and implemented for the model and the simulation study for the same is carried out using MATLAB. The proposed method discussed in the paper can adjust the controller parameters in response to changes in plant and disturbance in real-time by referring to the reference model that specifies the properties of the desired control system.Abstract
How to Cite
Downloads
Similar Articles
- K. Arunkumar, K. R. Shanthy, S. Lakshmisridevi, K. Thilagam, FR-CNN: The optimal method for slicing fifth-generation networks through the application of deep learning , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, A New Approach for Solving Bilevel Fractional/quadratic Green Transportation Problem by Implementing AI with Multi Choice Parameters Under Uncertainty , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- Binay Kumar Mahto, Rakesh Patel, Rajendra Bapna, Ajay Kumar Shukla, Development and Standardization of a Poly Herbal Formulation , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- J. Fathima Fouzia, M. Mohamed Surputheen, M. Rajakumar, Hybrid pigeon optimization-based feature selection and modified multi-class semantic segmentation for skin cancer detection (HPO-MMSS) , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- R. Sridevi, V. S. J. Prakash, Load aware active low energy adaptive clustering hierarchy for IoT-WSN , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- V Babydeepa, K. Sindhu, A hybrid feature selection and generative adversarial network for lung and uterus cancer prediction with big data , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RFSVMDD: Ensemble of multi-dimension random forest and custom-made support vector machine for detecting RPL DDoS attacks in an IoT-based WSN environment , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- M. Menaha, J. Lavanya, Crop yield prediction in diverse environmental conditions using ensemble learning , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- S. Kumar, M. Santhanalakshmi , R. Navaneethakrishnan, Content addressable memory for energy efficient computing applications , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Rama Rao J.V.G, Raja Gopal A.N.V.J, Ponnaganti S. Prasad, Illa V. Ram, Muthuvel B, Power quality improvement in BLDC motor drive using PFC converter , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 2 3 4 5 6 7 8 9 10 11 > >>
You may also start an advanced similarity search for this article.

