{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T12:45:17Z","timestamp":1781354717708,"version":"3.54.1"},"reference-count":43,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T00:00:00Z","timestamp":1630022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Energies"],"abstract":"<jats:p>This article presents the results of the optimization of steam generator control systems powered by mixtures of liquid fuels containing biofuels. The numerical model was based on the results of experimental research of steam generator operation in an open system. The numerical model is used to build control algorithms that improve performance, increase efficiency, reduce fuel consumption and increase safety in the full range of operation of the steam generator and the cogeneration system of which it is a component. In this research, the following parameters were monitored: temperature and pressure of the circulating medium, exhaust gas temperature, oxygen content in exhaust gas, percentage control of oil burner power. Two methods of controlling the steam generator were proposed: the classic one, using the PID regulator, and the advanced one, using artificial neural networks. The work shows how the model is adapted to the real system and the impact of the control algorithms on the efficiency of the combustion process. The example is considered for the implementation of advanced control systems in micro-, small- and medium-power cogeneration and trigeneration systems in order to improve their final efficiency and increase the profitability of implementation.<\/jats:p>","DOI":"10.3390\/en14175334","type":"journal-article","created":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T09:53:23Z","timestamp":1630058003000},"page":"5334","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Q-Learning Neural Controller for Steam Generator Station in Micro Cogeneration Systems"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4277-9801","authenticated-orcid":false,"given":"Krzysztof","family":"Lalik","sequence":"first","affiliation":[{"name":"Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Al. 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Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Martinez, D.I., Rubio, J.D.J., Garcia, V., Vargas, T.M., Islas, M.A., Pacheco, J., Gutierrez, G.J., Meda-Campa\u00f1a, J.A., Mujica-Vargas, D., and Aguilar-Iba\u00f1ez, C. (2021). Transformed Structural Properties Method to Determine the Controllability and Observability of Robots. Appl. Sci., 11.","DOI":"10.3390\/app11073082"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1002\/rnc.4396","article-title":"Robust neural network\u2013based tracking control and stabilization of a wheeled mobile robot with input saturation","volume":"29","author":"Huang","year":"2019","journal-title":"Int. J. Robust Nonlinear Control"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2307","DOI":"10.1049\/iet-cta.2017.0154","article-title":"Adaptive dynamic programming for robust neural control of unknown continuous-time non-linear systems","volume":"11","author":"Yang","year":"2017","journal-title":"IET Control Theory Appl."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"76900","DOI":"10.1109\/ACCESS.2018.2883596","article-title":"Theoretical application of a hybrid observer on altitude tracking of quadrotor losing GPS signal","volume":"6","year":"2018","journal-title":"IEEE Access"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"577749","DOI":"10.3389\/fnbot.2020.577749","article-title":"PD Control Compensation Based on a Cascade Neural Network Applied to a Robot Manipulator","volume":"14","author":"Soriano","year":"2020","journal-title":"Front. Neurorobot."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6945","DOI":"10.1007\/s00521-018-3520-3","article-title":"Recurrent fuzzy wavelet neural networks based on robust adaptive sliding mode control for industrial robot manipulators","volume":"31","author":"Yen","year":"2019","journal-title":"Neural Comput. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"106667","DOI":"10.1016\/j.ast.2021.106667","article-title":"Robust neural-network-based quasi-sliding-mode control for spacecraft-attitude maneuvering with prescribed performance","volume":"112","author":"Fu","year":"2021","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1109\/TCST.2007.903392","article-title":"MIMO robust control for HVAC systems","volume":"16","author":"Anderson","year":"2008","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1016\/j.conengprac.2010.03.006","article-title":"Normalized decoupling control for high-dimensional MIMO processes for application in room temperature control HVAC systems","volume":"18","author":"Shen","year":"2010","journal-title":"Control Eng. Pract."},{"key":"ref_11","first-page":"1","article-title":"Design of sliding mode and lQR controllers for an HVAC system","volume":"9","author":"Abtahi","year":"2013","journal-title":"Aerosp. Mech. J."},{"key":"ref_12","unstructured":"Haghighi, M.M., and Sangiovanni-Vincentelli, A.L. (2011). Modeling and Optimal Control Algorithm Design for HVAC Systems in Energy Efficient Buildings. [Master\u2019s Thesis, EECS Department, University of California]."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Shankar, G., Lakshmi, S., and Nagarjuna, N. (2015, January 12\u201314). Optimal load frequency control of hybrid renewable energy system using PSO and LQR. Proceedings of the 2015 International Conference on Power and Advanced Control Engineering (ICPACE), Bengaluru, India.","DOI":"10.1109\/ICPACE.2015.7274942"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1109\/TIE.2019.2897544","article-title":"LQR control of single-phase grid-tied PUC5 inverter with LCL filter","volume":"67","author":"Arab","year":"2019","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_15","unstructured":"Muratovich, Z.D., and Do, T.D. (2019, January 20\u201321). LQR Based SMC for Three-Phase-Inverter with LC Filter in Renewable Energy Conversion Systems. Proceedings of the 2019 International Conference on System Science and Engineering (ICSSE), Dong Hoi, Vietnam."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"115255","DOI":"10.1016\/j.apenergy.2020.115255","article-title":"Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings","volume":"271","author":"Homod","year":"2020","journal-title":"Appl. Energy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"16111","DOI":"10.1109\/ACCESS.2020.2966545","article-title":"Advanced fuzzy-logic-based context-driven control for HVAC management systems in buildings","volume":"8","author":"Escobar","year":"2020","journal-title":"IEEE Access"},{"key":"ref_18","first-page":"39","article-title":"Development of e-help manual using graphical user interface (gui) for battery management system (bms) in electric vehicle","volume":"13","author":"Amin","year":"2019","journal-title":"J. Adv. Manuf. Technol. (JAMT)"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"137","DOI":"10.2478\/aoter-2013-0039","article-title":"Analysis of operation of the gas turbine in a poligeneration combined cycle","volume":"34","author":"Kotowicz","year":"2013","journal-title":"Arch. Thermodyn."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Labella, A., Mestriner, D., Procopio, R., and Delfino, F. (2017, January 6\u20139). A simplified first harmonic model for the Savona Campus Smart Polygeneration Microgrid. Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC\/I CPS Europe), Milan, Italy.","DOI":"10.1109\/EEEIC.2017.7977491"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1584","DOI":"10.1016\/j.compchemeng.2009.05.009","article-title":"Predictive optimal management method for the control of polygeneration systems","volume":"33","author":"Collazos","year":"2009","journal-title":"Comput. Chem. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.energy.2013.03.070","article-title":"Study of optimal design of polygeneration systems in optimal control strategies","volume":"55","author":"Menon","year":"2013","journal-title":"Energy"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.enconman.2015.06.021","article-title":"A multi-agent decentralized energy management system based on distributed intelligence for the design and control of autonomous polygeneration microgrids","volume":"103","author":"Karavas","year":"2015","journal-title":"Energy Convers. Manag."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1303","DOI":"10.1016\/j.energy.2018.10.140","article-title":"Comparative analysis of selected thermoelectric generators operating with wood-fired stove","volume":"166","author":"Sornek","year":"2019","journal-title":"Energy"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.enconman.2016.05.091","article-title":"The development of a thermoelectric power generator dedicated to stove-fireplaces with heat accumulation systems","volume":"125","author":"Sornek","year":"2016","journal-title":"Energy Convers. Manag."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2018","DOI":"10.1016\/j.renene.2020.10.107","article-title":"CFD analysis and design optimization of an air manifold for a biomass boiler","volume":"163","author":"Bianco","year":"2021","journal-title":"Renew. Energy"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"El Rifai, K. (2009, January 10\u201312). Nonlinearly parameterized adaptive PID control for parallel and series realizations. Proceedings of the 2009 American Control Conference, St. Louis, MO, USA.","DOI":"10.1109\/ACC.2009.5159902"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1016\/j.jprocont.2006.03.002","article-title":"Analytical method of PID controller design for parallel cascade control","volume":"16","author":"Lee","year":"2006","journal-title":"J. Process. Control"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Rehrl, J., and Horn, M. (2011, January 28\u201330). Temperature control for HVAC systems based on exact linearization and model predictive control. Proceedings of the 2011 IEEE International Conference on Control Applications (CCA), Denver, CO, USA.","DOI":"10.1109\/CCA.2011.6044437"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Rehrl, J., Horn, M., and Reichhartinger, M. (2009, January 15\u201318). Elimination of limit cycles in hvac systems using the describing function method. Proceedings of the 48h IEEE Conference on Decision and Control (CDC) Held Jointly with 2009 28th Chinese Control Conference, Shanghai, China.","DOI":"10.1109\/CDC.2009.5400857"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1016\/j.asoc.2016.09.007","article-title":"An optimal adaptive robust PID controller subject to fuzzy rules and sliding modes for MIMO uncertain chaotic systems","volume":"52","author":"Mahmoodabadi","year":"2017","journal-title":"Appl. Soft Comput."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Pandey, S.K., Dey, J., and Banerjee, S. (2016, January 4\u20136). Design and real-time implementation of robust PID controller for Twin Rotor MIMO System (TRMS) based on Kharitonov\u2019s theorem. Proceedings of the 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), Delhi, India.","DOI":"10.1109\/ICPEICES.2016.7853106"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Dominik, I. (2014, January 8\u201310). Interval Type-2 Fuzzy Logic Control of NM70 Shape Memory Actuator. Proceedings of the Smart Materials, Adaptive Structures and Intelligent Systems, Newport, RI, USA.","DOI":"10.1115\/SMASIS2014-7606"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1007\/s42835-021-00698-5","article-title":"Study on the Influence of Parallel Fuzzy PID Control on the Regulating System of a Bulb Tubular Turbine Generator Unit","volume":"16","author":"Wang","year":"2021","journal-title":"J. Electr. Eng. Technol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1177\/1045389X15610907","article-title":"Type-2 fuzzy logic controller for position control of shape memory alloy wire actuator","volume":"27","author":"Dominik","year":"2016","journal-title":"J. Intell. Mater. Syst. Struct."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"84","DOI":"10.4028\/www.scientific.net\/SSP.177.84","article-title":"Fuzzy logic control of rotational inverted pendulum","volume":"Volume 177","author":"Dominik","year":"2011","journal-title":"Solid State Phenomena"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/0165-0114(94)00189-E","article-title":"Fuzzy controller: Design, evaluation, parallel and hierarchial combination with a pid controller","volume":"71","author":"Ketata","year":"1995","journal-title":"Fuzzy Sets Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"102091","DOI":"10.1016\/j.scs.2020.102091","article-title":"A novel hybrid modelling structure fabricated by using Takagi-Sugeno fuzzy to forecast HVAC systems energy demand in real-time for Basra city","volume":"56","author":"Homod","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Kozek, M. (2020, January 1\u20133). Transfer Learning algorithm in image analysis with Augmented Reality headset for Industry 4.0 technology. Proceedings of the 2020 International Conference Mechatronic Systems and Materials (MSM), Bialystok, Poland.","DOI":"10.1109\/MSM49833.2020.9201739"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Bartoszewicz, A., Kabzi\u0144ski, J., and Kacprzyk, J. (2020, January 21\u201328). Advanced, Contemporary Control: Proceedings of KKA 2020. Proceedings of the 20th Polish Control Conference, \u0141\u00f3d\u017a, Poland.","DOI":"10.1007\/978-3-030-50936-1"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"119866","DOI":"10.1016\/j.jclepro.2019.119866","article-title":"Transfer learning with deep neural networks for model predictive control of HVAC and natural ventilation in smart buildings","volume":"254","author":"Chen","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"8513","DOI":"10.1002\/er.5537","article-title":"Development and optimization of artificial neural network algorithms for the prediction of building specific local temperature for HVAC control","volume":"44","author":"Demirezen","year":"2020","journal-title":"Int. J. Energy Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1080\/23744731.2019.1680234","article-title":"Application of deep Q-networks for model-free optimal control balancing between different HVAC systems","volume":"26","author":"Ahn","year":"2020","journal-title":"Sci. Technol. Built Environ."}],"container-title":["Energies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1996-1073\/14\/17\/5334\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:53:46Z","timestamp":1760165626000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1996-1073\/14\/17\/5334"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,27]]},"references-count":43,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["en14175334"],"URL":"https:\/\/doi.org\/10.3390\/en14175334","relation":{},"ISSN":["1996-1073"],"issn-type":[{"value":"1996-1073","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,27]]}}}