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Fuzzy logic energy management system of food manufacturing processes
(2020) Baliuta, Serhii; Kopylova, Liudmyla; Kuievda, Yulia; Kuyevda, Valery; Kovalchuk, Olena
Introduction. The research is conducted to justify the method of increasing the efficiency of electrical power use in food production processes, which is based on the algorithms of fuzzy power management system. Materials and methods. The study is based on optimal and fuzzy control methods, such as Mamdani and Sugeno algorithms. Computer simulation was performed using MATLAB Simulink. Results and discussion. The control criterion of power supply of food production is formulated in the form of a functional minimization problem, which depends on the expected value of active and reactive power losses, active and reactive power losses at the level of secondary substations and individual load nodes. Maintaining energy efficient voltages in the power supply system nodes is chosen as a control task. It is determined the dependence of energy efficient voltages on the nominal voltage of the power system, the active resistance of its segments, the power and the coefficient of linearized static load characteristics at the network nodes, the equivalent active resistance, the nominal power, open circuit and short circuit losses of secondary substation transformers. To solve the control problem, an algorithm is synthesized using fuzzy controllers at the levels of the primary and secondary substations. In particular, it is determined that the input signals of the secondary substation fuzzy regulator should be the deviation from the energy efficient voltages and the rate of voltage change, and the output signals should be the transformer voltage and the actuation delay. Using numerical methods it is shown that this algorithm can reduce electricity losses in food production processes up to 7% compared to classical voltage regulation methods. Conclusions. The fuzzy system method under study ensures that energy-efficient voltage levels are maintained at the distribution network nodes when the voltage of the power source or the consumer loads are changed.
Identification of mathematical model of turbine generator unit in presence of uncertainty
(2021) Baliuta, Serhii; Chernenko, P. O.; Kuyevda, Valery; Kuievda, Yulia
An identification procedure of mathematical model of turbine generator unit in the presence of uncertainty is studied for using in the interconnected robust control automated system. The procedure is based on “worst-case” identification approach. The controlled object is modelled by the matrix transfer function with additive uncertainty. The identification consists of two stages: first is to identify transfer function with nominal parameters with the use of prediction error minimization algorithm, second – to determine weight function in additive uncertainty model using finding the worstcase log magnitude curve of uncertainties. Identification is performed in active way, determining datasets for each control channel from individual experiments. A linear frequency-modulated signal is selected as the input test disturbance. A simulation model of the controlled object is constructed and the numerical experiment is conducted using the identification procedure.

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