On Nonlinear Dynamics and Flight Control at High Angles of Attack With Uncertain Aerodynamics

2016 ◽  
Author(s):  
Mateus de Freitas Virgílio Pereira ◽  
Igor Afonso Acampora Prado ◽  
Davi Ferreira de Castro ◽  
José Manoel Balthazar ◽  
Roberto Gil Annes da Silva ◽  
...  
Keyword(s):  
Flight Control ◽  
Parametric Uncertainty ◽  
Linear Feedback ◽  
Fighter Aircraft ◽  
Generalized Polynomial ◽  
Hamilton Jacobi Bellman Equation ◽  
Optimal Linear ◽  
Hamilton Jacobi Bellman ◽  
High Angles Of Attack ◽  
Lyapunov Sense

In this paper we consider the flight dynamics of fighter aircraft at high angles of attack with uncertain aerodynamic coefficients. Stochastic parametric uncertainty is dealt with by employing spectral decomposition of the random variables by means of the generalized polynomial chaos expansion. We propose an optimal linear feedback strategy for the automatic pilot system to recover the aircraft from stall and provide acceptable dynamic response. Optimality of the proposed control law is proved by solving the Hamilton-Jacobi-Bellman equation and asymptotically stability of the controlled nonlinear aircraft model is guaranteed in the Lyapunov sense. Numerical results are verified with Monte-Carlo simulations.

scholarly journals Aircraft pitch control tracking with sliding mode control

2018 ◽  
Vol 7 (4.13) ◽  
pp. 62
Author(s):  
Nurhana M. Rouyan ◽  
Renuganth Varatharajoo ◽  
Samira Eshghi ◽  
Ermira Junita Abdullah ◽  
Shinji Suzuki
Keyword(s):  
Sliding Mode Control ◽  
Flight Control ◽  
Sliding Mode ◽  
Aerodynamic Characteristics ◽  
Control Methods ◽  
Fighter Aircraft ◽  
Pitch Control ◽  
Mode Control ◽  
Numerical Treatments ◽  
High Angles Of Attack

Sliding mode control (SMC) is one of the robust and nonlinear control methods. An aircraft flying at high angles of attack is considered nonlinear due to flow separations, which cause aerodynamic characteristics in the region to be nonlinear. This paper presents the comparative assessment for the flight control based on linear SMC and integral SMC implemented on the nonlinear longitudinal model of a fighter aircraft. The controller objective is to track the pitch angle and the pitch rate throughout the high angles of attack envelope. Numerical treatments are carried out on selected conditions and the controller performances are studied based on their transient responses. Obtained results show that both SMCs are applicable for high angles of attack.  

Interception of automated adversarial drone swarms in partially observed environments

2021 ◽  
pp. 1-14
Author(s):  
Daniel Saranovic ◽  
Martin Pavlovski ◽  
William Power ◽  
Ivan Stojkovic ◽  
Zoran Obradovic
Keyword(s):  
Bellman Equation ◽  
Pid Controllers ◽  
Partially Observed ◽  
Hamilton Jacobi Bellman Equation ◽  
Partial Feedback ◽  
Point Solution ◽  
Physical Limitations ◽  
Defensive Mechanisms ◽  
Hamilton Jacobi Bellman ◽  
New Framework

As the prevalence of drones increases, understanding and preparing for possible adversarial uses of drones and drone swarms is of paramount importance. Correspondingly, developing defensive mechanisms in which swarms can be used to protect against adversarial Unmanned Aerial Vehicles (UAVs) is a problem that requires further attention. Prior work on intercepting UAVs relies mostly on utilizing additional sensors or uses the Hamilton-Jacobi-Bellman equation, for which strong conditions need to be met to guarantee the existence of a saddle-point solution. To that end, this work proposes a novel interception method that utilizes the swarm’s onboard PID controllers for setting the drones’ states during interception. The drone’s states are constrained only by their physical limitations, and only partial feedback of the adversarial drone’s positions is assumed. The new framework is evaluated in a virtual environment under different environmental and model settings, using random simulations of more than 165,000 swarm flights. For certain environmental settings, our results indicate that the interception performance of larger swarms under partial observation is comparable to that of a one-drone swarm under full observation of the adversarial drone.

Multivariable adaptive distributed leader-follower flight control for multiple UAVs formation

2017 ◽  
Vol 121 (1241) ◽  
pp. 877-900 ◽  
Author(s):  
Y. Xu ◽  
Z. Zhen
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Flight Control ◽  
Control Strategy ◽  
Formation Control ◽  
Parametric Uncertainty ◽  
Lyapunov Theory ◽  
Formation Flight ◽  
Flight Control System ◽  
Multiple Uavs

ABSTRACTThe Unmanned Aerial Vehicles (UAVs) become more and more popular due to various potential application fields. This paper studies the distributed leader-follower formation flight control problem of multiple UAVs with uncertain parameters for both the leader and followers. This problem has not been addressed in the literature. Most of the existing literature considers the leader-follower formation control strategy with parametric uncertainty for the followers. However, they do not take the leader parametric uncertainty into account. Meanwhile, the distributed control strategy depends on less information interactions and is more likely to avoid information conflict. The dynamic model of the UAVs is established based on the aerodynamic parameters. The establishment of the topology structure between a collection of UAVs is based on the algebraic graph theory. To handle the parametric uncertainty of the UAVs dynamics, a multivariable model reference adaptive control (MRAC) method is addressed to design the control law, which enables follower UAVs to track the leader UAV. The stability of the formation flight control system is proved by the Lyapunov theory. Simulation results show that the proposed distributed adaptive leader-following formation flight control system has stronger robustness and adaptivity than the fixed control system, as well as the existing adaptive control system.

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