Kyushu University · Engineering
Professor Mostafa A. Rushdi's research lab focuses on innovative renewable energy systems, particularly wind energy harvesting through advanced technologies such as kite power systems and hybrid wind-solar towers. The lab specializes in the development of intelligent control systems, including nonlinear model predictive control for aerial vehicles like quadrotors, and leverages machine learning to model and optimize energy generation from experimental data. Their work emphasizes sustainable, low-impact energy solutions with high efficiency and scalability.
Figures are computed from collected data and may differ slightly.
In recent years, the increasing environmental problems, especially the issue of global warming, have motivated demand for a cleaner, more sustainable, and economically viable energy source. In this context, wind energy plays a significant role due to the small negative impact it has on the environment, which makes it among the most widespread potential sustainable renewable fuel nowadays. However, wind turbine control systems are important factors in determining the efficiency and cost-effective
Kites can be used to harvest wind energy at higher altitudes while using only a fraction of the material required for conventional wind turbines. In this work, we present the kite system of Kyushu University and demonstrate how experimental data can be used to train machine learning regression models. The system is designed for 7 kW traction power and comprises an inflatable wing with suspended kite control unit that is either tethered to a fixed ground anchor or to a towing vehicle to produce a
Wind solar towers constitute a fairly new scheme for harvesting renewable energy from solar and wind energy sources. In such a tower, solar radiation is collected and hot air is enforced to go fast through the tower, a process called thermal updraft, which fuels a wind turbine to generate power. Using vortex generators at the top of the tower creates a pressure difference, which increases the thermal updraft. In this work, we describe the setup of a wind solar tower system established at Kyushu
In this paper, we present the development of a non-linear model predictive controller for the trajectory tracking of a quadrotor using the CasADi optimization framework. The non-linear dynamic model of the quadrotor was derived using Newton–Euler equations, and the control algorithm and drone dynamics were wrapped in Matlab. The proposed controller was tested by simulating the tracking of a 3D helical reference trajectory, and its efficiency was evaluated in terms of numerical performance and tr
Kites can be used to harvest wind energy with substantially lower material and environmental footprints and a higher capacity factor than conventional wind turbines. In this paper, we present measurement data from seven individual tow tests with the kite system developed by Kyushu University. This system was designed for 7 kW traction power and comprises an inflatable wing of 6 m2 surface area with a suspended kite control unit that is towed on a relatively short tether of 0.4 m by a truck drivi
This paper introduces a new approach of harvesting energy from wind using a Kite Power System (KPS). Kite power systems are targeted herein because they have many advantages over other renewable energy sources, especially those related to wind energy. We capture the essential features of the tether connected to the kite via a lumped mass model and calculate the aerodynamic forces which cause tension in the tether. Work exerted by the tensile force in the tether is converted to electric power usi
Airborne wind energy (AWE) is an innovative renewable energy technology, with the potential to substantially reduce the cost of energy. This paper introduces a solution for one of the main challenges of AWE systems, which is the automated reliable launching of the airborne system component. Our launch system configuration consists of a rigid-wing flying object (aircraft) equipped with a VTOL subsystem and launched vertically, with the fuselage also directed vertically. We formulate the Transitio
In this paper, we describe a machine learning (ML) approach for estimating interface orientation in multiphase flow using the volume of fluid (VOF) method on a uniform Cartesian mesh. By using complex shapes generated with the parametric radial star formula during training, we significantly improve prediction accuracy without increasing the network's structural complexity or processing cost. Our key contribution is the development of a robust ML model capable of reliably predicting interface ori
The phenomenon of spread of a (pathogenic) virus involves many physical variables, and is not amenable to satisfactory analysis via conventional methods. Dimensional Analysis (DA) is singled out as a simple and accessible way that can determine (at least qualitatively) how virus spread is related to seven physical quantities that are thought to influence it. However, classical DA deduces four dimensionless products only, none of which incorporates temperature and humidity, despite the obvious re
We utilize the electromagnetically-oriented LTI∅ dimensional basis in the matrix solution of dimensional-analysis (DA) problems involving mainly electromagnetic quantities, whether these quantities are lumped or distributed. Representations in the LTI∅ basis (compared with the standard MLTI basis) are more informative and much simpler. Moreover, matrix DA computations employing the LTI∅ basis are more efficient and much less error prone. Extensive discussions of two demonstrative examples expose
The traction force of a kite system can be utilized for extracting energy from high-altitude wind. This paper discusses a system identification algorithm derived to obtain real-time governing equations for the kite system based on real-flight data, obtained from a 6 m2 kite power system developed in Kyushu University as an airborne wind energy project. The paper presents the system set-up, the design, the experimental results, a system identification algorithm, and the parameters identified for
This paper describes the electromagnetically-oriented 𝐿𝑇𝐼∅ dimensional basis that is based on the ref- erence dimensions of Length (𝐿), Time (T), Electric Current (𝐼), and Electric Potential (∅). We utilize this basis in the matrix solution of dimensional-analysis (DA) problems involving mainly electromagnetic quantities. Rep- resentations of electromagnetic quantities in the
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