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Special attention is given to vertical takeoff and landing air vehicles due to their unique capabilities and versatile missions. The main problem here is control effectiveness at low flight speeds and transition maneuvers because of the inherent instability. RMIT is a small sized tail-sitter ducted fan air vehicle with a particular configuration layout, multiple control surfaces, low weight, and high-speed flight capability. In the current study, a comprehensive nonlinear model is firstly developed for RMIT, followed by a validation process. This model consists of all parts including aerodynamic forces and moments, control surfaces term together with the gravity and driving fan forces.... 

Attitude control of a novel regional truss-braced wing (TBW) aircraft with low stability characteristics is addressed in this paper using Reinforcement Learning (RL). In recent years, RL has been increasingly employed in challenging applications, particularly, autonomous flight control. However, a significant predicament confronting discrete RL algorithms is the dimension limitation of the state-action table and difficulties in defining the elements of the RL environment. To address these issues, in this paper, a detailed mathematical model of the mentioned aircraft is first developed to shape an RL environment. Subsequently, Q-learning, the most prevalent discrete RL algorithm, will be...