Publication: Modeling and control of the ducted fan lift system
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Date
2023-09-01
Authors
Jiang, Hanjie
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Abstract
Urban air mobility is an emerging concept that has been proposed in recent years which encompasses a diverse range of Vertical TakeOff and Landing (VTOL) vehicles that function similar to passenger-carrying drones for on-demand transportation. Among them, the car-like VTOL is favorable due to its compact configuration, safe rotors, high user affinity, and technological fashion. These characteristics are frequently derived from the Ducted Fan Lift System (DFLS). Compared to an electrically powered DFLS, a fuel-engine-powered DFLS is more likely to meet the requirements of high power and high energy density, thereby delivering superior flight performance. Two-stroke aviation piston engine-driven DFLSs are multivariable with highly non linear dynamics, which poses challenges for control engineers in both modeling and control. Firstly, it is difficult to accurately model and evaluate the aerodynamic performance of a ducted fan in a rapid and theoretical manner. Secondly, constructing a general dynamic model for the two-stroke engine control application is a daunting task. Lastly, the engine-driven DFLS is a complex, multivariable system with tightly coupled nonlinear dynamics, which creates additional obstacles for effective control. To
address the before-mentioned problems, this thesis developed a ducted fan model using blade element theory and momentumtheorytosupport the rapid scheme demonstration and control study. Meanwhile, a general Mean Value Engine Model (MVEM) of two stroke aviation piston engines was developed, which is represented by appropriate empirical equations that require little engine data and easily capture the main dynamics. Based onthetwoproposedmodels, this thesis developed an Adaptive Model Predictive Control (AMPC) strategy with an associated Linear Parameter Varying (LPV) model for controlling the engine-driven DFLS. The LPV model is derived from an Radial Basis Function (RBF) network model trained with the data from the proposed general MVEM. The proposed AMPC was selected in the Air-Fuel Ratio (AFR) control study of HIRTH-3203 for better precision and faster response, compared with the control
strategy using Deterministic Policy Gradient (DPG) algorithm. The ducted fan of a 1:3 scale verifier for a flying car scheme was designed and evaluated using the proposed method, a numerical method, and a bench test. Compared to the test results, the proposed model showed its precise performance with an average difference of 1.9%. The proposed engine model was validated using HIRTH-3203 and NU-57 laboratory data, and the results illustrated that the issues of fitting simplicity and general applicability were well addressed. The efficiency of the proposed RBF-based AMPC was demonstrated through numerical simulations of a vertical take-off thrust preparation process for the DFLS. The simulation results indicate that the proposed AMPC method can effectively control the DFLS thrust with a relative error below 3.5%.