Control of the longitudinal flight dynamics of an UAV using adaptive backstepping

Abstract

An adaptive backstepping approach is used to control the longitudinal dynamics of an Unmanned Air Vehicle (UAV). The nonlinear controller designed makes the system follow references in the aerodynamic velocity and flight path angle, using the elevator deflections and the thrust as actuators. Moreover, the (global) solution is valid for all the flight envelope, since it is based on a general nonlinear model. The adaptation scheme proposed allowed us to design an explicit controller with a minimal knowledge of the aircraft aerodynamics. Simulations are included for a realistic UAV model that includes actuator saturation.

Adaptive Control for Aircraft Longitudinal Dynamics with Thrust Saturation

“…The velocity controller of Proposition 3.1 improves the one previously presented by the authors in [24]. This new feedback law is able to achieve global stability using a simpler control law with a lower computational burden.…”

“…The controller formulation is based on a previous result by the authors presented in [25]. This is, in turn, an improvement of a previous full-state design given in [24].…”

“…The basis of this work can be found in the conference papers [24,25]. The first conference paper contains the initial attempt to solve the problem using a full-state feedback design.…”

Lyapunov‐based trajectory tracking controller for a fixed‐wing unmanned aerial vehicle in the presence of wind

“…For instance, a backstepping design has been used in [15] for the purposes of stabilization and trajectory tracking of a small tiltrotor-based aircraft model. Other backstepping-based flight controllers are described in [18,19].…”

Nonlinear Dynamics and Control of Aerial Robots

“…In particular, nonlinear control of fixed-wing UAVs has attracted considerable research efforts during recent years both for civilian and military purposes. The control approaches developed for fixedwing UAVs include gain scheduling, model predictive control, backstepping, sliding mode, nested saturation, fuzzy control, H ∞ control, dynamic inversion based control, model reference adaptive control, and model based fault tolerant control [1][2][3][4][5][6][7][8][9][10][11][12].…”