Journal Article10.1016/S0360-1285(03)00058-3
Artificial intelligence for the modeling and control of combustion processes: a review
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TL;DR: How AI techniques might play an important role in modeling and prediction of the performance and control of combustion process is illustrated to testify to the potential of AI as a design tool in many areas of combustion engineering.
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About: This article is published in Progress in Energy and Combustion Science. The article was published on 01 Jan 2003. The article focuses on the topics: Expert system & Systems modeling.
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Citations
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Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source
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Artificial intelligence techniques for sizing photovoltaic systems: A review
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References
Application of Fuzzy Control to Internal Combustion Engines
TL;DR: In this article, fuzzy control was applied to the diesel engine and the level of robustness of fuzzy control is investigated in comparison with PI and LQI control methods, and it was found that fuzzy control showed the highest level of reliability and a much faster control response compared with the two other methods of control.
8
Fast response distributed parameter fluidized bed reactor model for propylene partial oxidation using feed-forward neural network methods
TL;DR: In this article, the authors used a neural network model to simulate the performance of a fluidized-bed reactor for the partial oxidation of propylene to acrolein, where the flow patterns for the bubble and emulsion phases in each cell are assumed to be plug-flow and perfectly mixed, respectively.
8
Development and implementation of a neural knock detector using constructive learning methods
Stefan Ortmann,Manfred Glesner +1 more
TL;DR: The world-wide demands for reasonable fuel consumption and reduced engine emissions force engine developers to improve the combustion process to meet these demands.
5
Modeling, plant uncertainties, and fuzzy logic sliding control of gaseous systems
TL;DR: The active control problem of gaseous processes such as primary air atmospheric-suction and forced-draft supply of air for fuel combustion is addressed and a fuzzy-logic-based inference engine realizes the adaptive law that tunes the switched gain to the smallest value that verifies the sliding condition.
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•Journal Article
Application of a neural-network-based controller on an industrial chain grate stoker fired boiler
TL;DR: In this article, a neural network-based controller for coal-firing stoker was developed to provide initial estimates of the near optimum settings required for the coal feed and airflow rates as well as appropriate staging of these variables during load-following conditions.
5