Mathematical Model of Adaptive Control in Fuel Supply Logistic System

  • Ekaterina KasatkinaEmail author
  • Denis Nefedov
  • Ekaterina Saburova
Conference paper
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 199)


Optimal control of fuel supply system boils down to choosing an energy development strategy which provides consumers with the most efficient and reliable fuel and energy supply. As a part of the program on switching the heat supply distributed control system of the Udmurt Republic to renewable energy sources, an “Information-analytical system of regional alternative fuel supply control” was developed. Information-analytical system is designed to dealing with problems of optimal control of regional distributed fuel supply system of the Udmurt Republic. In order to increase effective the performance of regional fuel supply system a modification of information-analytical system and extension of its set of functions using the methods of quick responding when emergency occurs are required. The object of the research is the logistic distributed fuel supply system consisting of three interconnected levels: raw material accumulation points, fuel preparation points and fuel consumption points, which are heat sources. The mathematical model of optimal control of fuel supply logistic system is introduced. Emergencies which occur on any one of these levels demand the control of the whole system to reconfigure. The paper demonstrates models and algorithms of optimal control in case of emergency involving break down of such production links of logistic system as raw material accumulation points and fuel preparation points. The implementation of the developed algorithms is based on the usage of genetic optimization algorithms, which made it possible to obtain a more accurate solution in less time. The developed models and algorithms are integrated into the information-analytical system that enables to provide effective control of alternative fuel supply of the Udmurt Republic in case of emergency.


Genetic algorithm Optimal control Fuel supply Mathematical modeling Alternative energy 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Kalashnikov Izhevsk State Technical UniversityIzhevskRussia

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