Underactuated Unmanned Aerial Vehicle Research Articles

Quaternion-based adaptive backstepping fast terminal sliding mode control for quadrotor UAVs with finite time convergence

This paper proposes a novel quaternion-based approach for tracking the translation (position and linear velocity) and rotation (attitude and angular velocity) trajectories of underactuated Unmanned Aerial Vehicles (UAVs). Quadrotor UAVs are challenging regarding accuracy, singularity, and uncertainties issues. Controllers designed based on unit-quaternion are singularity-free for attitude representation compared to other methods (e.g., Euler angles), which fail to represent the vehicle's attitude at multiple orientations. Quaternion-based Adaptive Backstepping Control (ABC) and Adaptive Fast Terminal Sliding Mode Control (AFTSMC) are proposed to address a set of challenging problems. A quaternion-based ABC, a superior recursive approach, is proposed to generate the necessary thrust handling unknown uncertainties and UAV translation trajectory tracking. Next, a quaternion-based AFTSMC is developed to overcome parametric uncertainties, avoid singularity, and ensure fast convergence in a finite time. Moreover, the proposed AFTSMC is able to significantly minimize control signal chattering, which is the main reason for actuator failure and provide smooth and accurate rotational control input. To ensure the robustness of the proposed approach, the designed control algorithms have been validated considering unknown time-variant parametric uncertainties and significant initialization errors. The proposed techniques have been compared to state-of-the-art control technique.

Continual online learning-based optimal tracking control of nonlinear strict-feedback systems: application to unmanned aerial vehicles

A novel optimal trajectory tracking scheme is introduced for nonlinear continuous-time systems in strict feedback form with uncertain dynamics by using neural networks (NNs). The method employs an actor-critic-based NN backstepping technique for minimizing a discounted value function along with an identifier to approximate unknown system dynamics that are expressed in augmented form. Novel online weight update laws for the actor and critic NNs are derived by using both the NN identifier and Hamilton-Jacobi-Bellman residual error. A new continual lifelong learning technique utilizing the Fisher Information Matrix via Hamilton-Jacobi-Bellman residual error is introduced to obtain the significance of weights in an online mode to overcome the issue of catastrophic forgetting for NNs, and closed-loop stability is analyzed and demonstrated. The effectiveness of the proposed method is shown in simulation by contrasting the proposed with a recent method from the literature on an underactuated unmanned aerial vehicle, covering both its translational and attitude dynamics.

Robust nonlinear 3D control of an inverted pendulum balanced on a quadrotor

This paper addresses the nonlinear control problem of balancing an inverted pendulum on an underactuated unmanned aerial vehicle. In view of the system’s slow and quick transients, a convenient error transformation is employed to render the attitude subsystem less sensitive to translational errors. Linearizations are not involved, making this controller suitable beyond the limited scope of trim maneuvers. Furthermore, the controller features an adaptive bounded law that is used to compensate for unknown exogenous perturbations. The Lyapunov-based control design is rooted in an integral backstepping process, wherein the origin of the closed-loop total system error is shown to be almost globally asymptotically stable. Simulation results are presented to validate our strategy, and experimental results are also provided to demonstrate its accuracy and robustness.

Dynamic Target Tracking of Unmanned Aerial Vehicles Under Unpredictable Disturbances

This study proposes an image-based visual servoing (IBVS) method based on a velocity observer for an unmanned aerial vehicle (UAV) for tracking a dynamic target in Global Positioning System (GPS)-denied environments. The proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target. A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is proposed. The depth model ensures image feature accuracy and image trajectory smoothness in rotating target tracking. The relative velocities of the UAV and the dynamic target are estimated using the proposed velocity observer. Thanks to the velocity observer, translational velocity measurements are not required, and the control chatter caused by noise-containing measurements is mitigated. An integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the anti-disturbance ability. The stability of the velocity observer and IBVS controller is analyzed using the Lyapunov method. Comparative simulations and multistage experiments are conducted to illustrate the tracking stability, anti-disturbance ability, and tracking robustness of the proposed method with a dynamic rotating target.

A Homography-Based Visual Servo Control Approach for an Underactuated Unmanned Aerial Vehicle in GPS-Denied Environments

This paper proposes a homography-based visual servo control approach for the stabilization of underactuated unmanned aerial vehicles in GPS-denied environments. A virtual homography matrix is proposed, and a new visual error vector is defined to obtain the passivity-like visual error equation. In addition, a homography-based online translation velocity estimator and a nonlinear backstepping visual servo control approach are addressed to promote fast maneuvering without linear velocity feedback. Unlike conventional homography-based visual servo control solutions that only guarantee the local stability in the equilibrium, the proposed control scheme can get the global stability in large offset. Simulation and experimental tests with a realistic quadrotor subject to the measurement noise are carried out to verify the robustness and performance of the control approach. In addition, the autonomous tracking experiment when the target speed is unpredictable are also reported.

Distributed 3D Navigation of Swarms of Non-Holonomic UAVs for Coverage of Unsteady Environmental Boundaries

A team of non-holonomic constant-speed under-actuated unmanned aerial vehicles (UAVs) with lower-limited turning radii travel in 3D. The space hosts an unknown and unpredictably varying scalar environmental field. A space direction is given; this direction and the coordinate along it are conditionally termed as the “vertical” and “altitude”, respectively. All UAVs should arrive at the moving and deforming isosurface where the field assumes a given value. They also should evenly distribute themselves over a pre-specified range of the “altitudes” and repeatedly encircle the entirety of the isosurface while remaining on it, each at its own altitude. Every UAV measures only the field intensity at the current location and both the Euclidean and altitudinal distances to the objects (including the top and bottom of the altitudinal range) within a finite range of visibility and has access to its own speed and the vertical direction. The UAVs carry no communication facilities, are anonymous to one another, and cannot play distinct roles in the team. A distributed control law is presented that solves this mission under minimal and partly inevitable assumptions. This law is justified by a mathematically rigorous global convergence result; computer simulation tests confirm its performance.

Dynamic Attitude Planning for Trajectory Tracking in Thrust-Vectoring UAVs

This paper addresses the trajectory tracking control problem for underactuated unmanned aerial vehicles (UAVs), with specific focus on vehicles with thrust-vectoring capabilities. According to the different actuation mechanisms, the most common UAV platforms can achieve only a partial decoupling of attitude and position tasks. Since position tracking is of utmost importance for applications involving aerial vehicles, we propose a control scheme in which position tracking is the primary objective. To this end, this paper exploits the concept of attitude planner, a dynamical system through which the desired attitude reference is processed to guarantee the satisfaction of the primary objective: The attitude tracking task is considered as a secondary objective, which can be realized as long as the desired trajectory satisfies specific trackability conditions.

Full State Tracking and Formation Control for Under-Actuated VTOL UAVs

In this paper, a coupled-attitude based trajectory tracking scheme is proposed to track both the position and attitude of under-actuated unmanned aerial vehicles, and its application on formation control is further demonstrated. An intermediate attitude which is composed of the desired attitude and position information is designed in a two-stage framework, wherein the first stage is the controller design of a translational subsystem and the second stage is that of an attitude subsystem. By virtue of the intermediate attitude, trajectory tracking which includes both attitude and position is realized. The proposed intermediate attitude can be viewed as a bridge connecting the position and attitude motion, and it is a new approach for both single and multiple under-actuated rigid bodies’ control. Based on the approach of coupled-attitude-based trajectory tracking, both the set point stabilization and formation tracking tasks for under-actuated vertical takeoff and landing vehicles over a directed acyclic graph can be achieved. The performances of the proposed control laws are illustrated through numerical simulations.

Optimization of fuzzy membership functions via PSO and GA with application to quad rotor

Quad rotor is a renowned underactuated Unmanned Aerial Vehicle (UAV) with widespread military and civilian applications. Despite its simple structure, the vehicle suffers from inherent instability. Therefore, control designers always face formidable challenge in stabilization and control goal. In this paper fuzzy membership functions of the quad rotor’s fuzzy controllers are optimized using nature-inspired algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). Finally, the results of the proposed methods are compared and a trajectory is defined to verify the effectiveness of the designed fuzzy controllers based on the algorithm with better results.

Output feedback image-based visual servoing control of an underactuated unmanned aerial vehicle

In this article, image-based visual servoing control of an underactuated unmanned aerial vehicle is considered for the three-dimensional translational motion. Taking into account the low quality of accelerometers’ data, the main objective of this article is to only use information of rate gyroscopes and a camera, as the sensor suite, in order to design an image-based visual servoing controller. Kinematics and dynamics of the unmanned aerial vehicle are expressed in terms of visual information, which make it possible to design dynamic image-based visual servoing controllers without using linear velocity information obtained from accelerometers. Image features are selected through perspective image moments of a flat target plane in which no geometric information is required, and therefore, the approach can be applied in unknown environments. Two output feedback controllers that deal with uncertainties in dynamics of the system related to the motion of the target and also unknown depth information of the image are proposed using a linear observer. Stability analysis guarantees that the errors of the system remain uniformly ultimately bounded during a tracking mission and converge to 0 when the target is stationary. Simulation results are presented to validate the designed controllers.

AN ADAPTIVE SCHEME FOR IMAGE-BASED VISUAL SERVOING OF AN UNDERACTUATED UAV

An image-based visual servoing (IBVS) method is proposed for controlling the 3D translational motion and the yaw rotation of a quadrotor. The dynamic model of this unmanned aerial vehicle (UAV) is considered at the design stage to account for its underactuation. In contrast with previous IBVS methods for underactuated UAVs, which used spherical image moments as visual features, the proposed controller makes use of appropriately defined perspective moments. As a consequence, we gain a clear improvement in performance, as satisfactory trajectories are obtained in both image and Cartesian space. In addition, an adaptation mechanism is included in the controller to achieve robust performance in spite of uncertainties related to the depth of the image features and to the dynamics of the robot. Simulation results in both nominal and perturbed conditions are presented to validate the proposed method.

Haptic-based bilateral teleoperation of underactuated Unmanned Aerial Vehicles

AbstractThe bilateral teleoperation of underactuated aerial vehicles is addressed. A force feedback joystick is used to remotely pilot the aircraft and reflect an image of the environment to the operator. This feedback is a virtual force, function of the distance to an obstacle or the rate of approaching it. It can be computed using the measurements of on-board sensors (i.e. telemetric or optic flow). Input to State Stability of the teleoperation loop with respect to bounded or dissipative virtual environment forces is established based on Lyapunov analysis.