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On the Toroidal Comaximal Graph of Lattices
Javaheri, Khadijeh Ahmad,Parsapour, Atossa Department of Mathematics 2018 Kyungpook mathematical journal Vol.58 No.3
In this paper, we study the toroidality of the comaximal graphs of a finite lattice.
When the Comaximal Graph of a Lattice is Toroidal
Afkhami, Mojgan,Javaheri, Khadijeh Ahmad,Khashyarmanesh, Kazem Department of Mathematics 2016 Kyungpook mathematical journal Vol.56 No.3
In this paper we investigate the toroidality of the comaximal graph of a finite lattice.
Modeling and fuzzy control of the engine coolant conditioning system in an IC engine test bed
Seyed Saeid Mohtasebi,Farzad A. Shirazi,Ahmad Javaheri,Ghodrat Hamze Nava 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.11
Mechanical and thermodynamical performance of internal combustion engines is significantly affected by the engine working temperature. In an engine test bed, the internal combustion engines are tested in different operating conditions using a dynamometer. It is required that the engine temperature be controlled precisely, particularly in transient states. This precise control can be achieved by an engine coolant conditioning system mainly consisting of a heat exchanger, a control valve, and a controller. In this study, constitutive equations of the system are derived first. These differential equations show the second- order nonlinear time-varying dynamics of the system. The model is validated with the experimental data providing satisfactory results. After presenting the dynamic equations of the system, a fuzzy controller is designed based on our prior knowledge of the system. The fuzzy rules and the membership functions are derived by a trial and error and heuristic method. Because of the nonlinear nature of the system the fuzzy rules are set to satisfy the requirements of the temperature control for different operating conditions of the engine. The performance of the fuzzy controller is compared with a PI one for different transient conditions. The results of the simulation show the better performance of the fuzzy controller. The main advantages of the fuzzy controller are the shorter settling time, smaller overshoot, and improved performance especially in the transient states of the system.