Development of algorithms for diagnostics as well as control of biomass gasification and combustion processes

Laura Yesmakhanova (), Waldemar Wójcik, Seitzhan Orynbayev (), Indira Shedreyeva () and Martebe Zhankuanyshev ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 2, 3236-3253

Abstract: This study examines the development of algorithms for diagnosis as well as the control of biomass gasification and combustion processes. The scientific work is grounded in theory and research findings from both laboratory stations and industrial facilities that use biomass as fuel, typically co-fired with coal after pre-crushing. The practical significance of the work is that biomass was converted into gas or solid form to provide additional fuel during combustion at laboratory stations. The work specifically focuses on diagnosing complex processes, including biomass gasification and its co-combustion in solid form. The experimental studies have been carried out with a deep theoretical analysis, and the material presented in the study contains concise results concerning the diagnosis and control of gasification and combustion processes, both at laboratory and industrial scales. The research is carried out on laboratory and industrial scales using research equipment, including the flame control system, which allowed obtaining the measurement results necessary to analyze various diagnostic algorithms, which were an element necessary to develop the control of a complex object, using the process of co-combustion of coal dust and biomass as an example. The obtained results, both from laboratory bench tests and industrial conditions, enabled us to develop robust control using hybrid neural network structures. Scientific novelty–using robust control algorithms, the efficiency of the combustion process of both coal dust and co-combustion of coal dust with biomass is increased. To achieve this goal, flexible control of the complex process is used.

Keywords: Biomass; Borescope; Combustion process; Control; Diagnostics; Gasification process; Neural networks. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:aac:ijirss:v:8:y:2025:i:2:p:3236-3253:id:5992

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