Видання НТУ "ХПІ"
Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/62886
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Документ Maximum power point tracking improvement using type-2 fuzzy controller for wind system based on the double fed induction generator(Національний технічний університет "Харківський політехнічний інститут", 2024) Kaddache, M.; Drid, S.; Khemis, A.; Rahem, D.; Chrifi-Alaoui, L.In this paper, to maximize energy transmission in wind power system, various Maximum Power Point Tracking (MPPT) approaches are available. Among these techniques, we have proposed the one based on typical fuzzy logic. Despite the somewhat reduced performance of fuzzy MPPT. For a number of reasons, fuzzy MPPT can replace conventional optimization techniques. In practice, the effectiveness of conventional MPPT methods depends mainly on the accuracy of the information given and the wind speed or knowledge of the aerodynamic properties of the wind system. Novelty. Our new MPPT for monitoring the maximum power point has been proposed. We developed an algorithm to improve control performance and govern the stator’s developed active and reactive power using the typical fuzzy logic 2 and enable robust control of a grid-connected, doubly fed induction generator. Purpose. MPPT which implies the wind turbine’s rotating speed should be modified in real time to capture the most wind energy, is necessary to achieve high efficiency for wind energy conversion, according to the aerodynamic characteristics of the wind turbine. Methods. Developing a mathematical model for a wind energy production system is complex, can be strongly affected by wind variation and is a non-linear problem. Thanks to these characteristics, thus, the Lyapunov technique is combined with a sliding mode control to ensure overall asymptotic stability and robustness with regard to parametric fluctuations in order to accomplish this goal. We contrasted our fuzzy type-2 algorithm’s performance with that of the fuzzy type-1 and Perturbation & Observation (P&O) suggested in the literature. Practical value. The simulation results demonstrate that the control performance is satisfactory when using the fuzzy logic technique. From these results, it can be said for the optimization of energy conversion in wind systems, the fuzzy type-2 technique may offer a workable option. Since it presents a great possibility to avoid problems either technical or economics linked to conventional strategies.Документ Model reference adaptive system speed estimator based on type-1 and type-2 fuzzy logic sensorless control of electrical vehicle with electrical differential(Національний технічний університет "Харківський політехнічний інститут", 2023) Khemis, Abderrahmane; Boutabba, Tarek; Drid, SaidIn this paper, a new approach for estimating the speed of in-wheel electric vehicles with two independent rear drives is presented. Currently, the variable-speed induction motor replaces the DC motor drive in a wide range of applications, including electric vehicles where quick dynamic response is required. This is now possible as a result of significant improvements in the dynamic performance of electrical drives brought about by technological advancements and development in the fields of power commutation devices, digital signal processing, and, more recently, intelligent control systems. The system’s reliability and robustness are improved, and the cost, size, and upkeep requirements of the induction motor drive are reduced through control strategies without a speed sensor. Successful uses of the induction motor without a sensor have been made for medium- and high-speed operations. However, low speed instability and instability under various charge perturbation conditions continue to be serious issues in this field of study and have not yet been effectively resolved. Some application such as traction drives and cranes are required to maintain the desired level of torque down to low speed levels with uncertain load torque disturbance conditions. Speed and torque control is more important particularly in motor-in-wheel traction drive train configuration where vehicle wheel rim is directly connected to the motor shaft to control the speed and torque. Novelty of the proposed work is to improve the dynamic performance of conventional controller used of model reference adaptive system speed observer using both type-1 and type-2 fuzzy logic controllers. Purpose. In proposed scheme, the performance of the engine is being controlled, fuzzy logic controller is controlling the estimate rotor speed, and results are then compared using type-1 and type-2. Method. For a two-wheeled motorized electric vehicle, a high-performance sensorless wheel motor drive based on both type-2 and type-1 fuzzy logic controllers of the model reference adaptive control system is developed. Results. Proved that, using fuzzy logic type-2 controller the sensorless speed control of the electrical differential of electric vehicle EV observer, much better results are achieved. Practical value. The main possibility of realizing reliable and efficient electric propulsion systems based on intelligent observers (type-2 fuzzy logic) is demonstrated. The research methodology has been designed to facilitate the future experimental implementation on a digital signal processor.