L 1 adaptive control of a generic hypersonic vehicle model with a blended pneumatic and thrust vectoring control strategy

2016 ◽  
Vol 60 (3) ◽  
Author(s):  
Qi Chen ◽  
Jing Wan ◽  
Jianliang Ai
2019 ◽  
Vol 95 ◽  
pp. 45-57 ◽  
Author(s):  
Hao An ◽  
Hongwei Xia ◽  
Guangcheng Ma ◽  
Changhong Wang

2005 ◽  
Author(s):  
Kevin P. Groves ◽  
Andrea Serrani ◽  
Stephen Yurkovich ◽  
Michael A. Bolender ◽  
David B. Doman

2021 ◽  
pp. 1-31
Author(s):  
S.H. Derrouaoui ◽  
Y. Bouzid ◽  
M. Guiatni

Abstract Recently, transformable Unmanned Aerial Vehicles (UAVs) have become a subject of great interest in the field of flying systems, due to their maneuverability, agility and morphological capacities. They can be used for specific missions and in more congested spaces. Moreover, this novel class of UAVs is considered as a viable solution for providing flying robots with specific and versatile functionalities. In this paper, we propose (i) a new design of a transformable quadrotor with (ii) generic modeling and (iii) adaptive control strategy. The proposed UAV is able to change its flight configuration by rotating its four arms independently around a central body, thanks to its adaptive geometry. To simplify and lighten the prototype, a simple mechanism with a light mechanical structure is proposed. Since the Center of Gravity (CoG) of the UAV moves according to the desired morphology of the system, a variation of the inertia and the allocation matrix occurs instantly. These dynamics parameters play an important role in the system control and its stability, representing a key difference compared with the classic quadrotor. Thus, a new generic model is developed, taking into account all these variations together with aerodynamic effects. To validate this model and ensure the stability of the designed UAV, an adaptive backstepping control strategy based on the change in the flight configuration is applied. MATLAB simulations are provided to evaluate and illustrate the performance and efficiency of the proposed controller. Finally, some experimental tests are presented.


Author(s):  
Fatma Ezzahra Rhili ◽  
Asma Atig ◽  
Ridha Ben Abdennour ◽  
Fabrice Druaux ◽  
Dimitri Lefebvre

In this study, an adaptive control based on fuzzy adapting rate for neural emulator of nonlinear systems having unknown dynamics is proposed. The indirect adaptive control scheme is composed by the neural emulator and the neural controller which are connected by an autonomous algorithm inspired from the real-time recurrent learning. In order to ensure stability and faster convergence, a neural controller adapting rate is established in the sense of the continuous Lyapunov stability method. Numerical simulations are included to illustrate the effectiveness of the proposed method. The performance of the proposed control strategy is also demonstrated through an experimental simulation.


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