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This paper deals with the design and implementation of a nonlinear control strategy to solve the path tracking problem for an Autonomous Underwater Vehicle (AUV) under model uncertainties and external disturbances. First, the AUV model is transformed into the so-called regular form by an appropriate selection of state variables. The method is based on the second-order sliding mode technique known as Generalized Super-Twisting Algorithm (GSTA) introducing the design of an auto-adjustable gain controller which offers a way to ensure robustness to modeling errors and bounded external disturbances. The control law is designed to maintain a minimum margin of error in the trajectory tracking of the AUV even in the presence of damping and buoyancy disturbances. Finally, experimental results are also provided to illustrate the performances of the closed-loop system using the proposed controller.

Admittance control is mostly used for human-robot interaction. When the admittance control is applied in the task space, it needs the Jacobian matrix. When the admittance control is in joint space, it requires inverse kinematics of the robot. In this paper, the admittance control is modified to only use the orientations of the end effector to generate the desired joint angles to avoid inverse kinematics. The classical PD control is also modified with adaptive compensation and sliding mode compensation. The stability of these two PD controllers are proven. Real time experiments are presented for with a 2-DOF pan and tilt robot and a 4-DOF exoskeleton. The experiment results show the effectiveness of the proposed controllers.

Path following is a basic autonomous navigation capability for UAV’s and in this paper we present a nonlinear 3D path following kinematic controller. In order to solve this problem, we use the typical multi-loop control structure in which the navigation controller directs the aircraft to the desired path, while the inner loop acts as an autopilot which stabilizes the nonlinear dynamics and tracks the command generated by the outer loop. Under the assumption that the autopilot is well tuned and the airspeed, fight-path angle, and bank angle states converge to the desired response to their commanded values, we use a kinematic model as a suitable control model for the fixed wing UAV. With the introduction of a virtual target, the proposed Lyapunov based kinematic controller for outer loop can steer the UAV asymptotically to approach the desired path. The proposed controller is validated in a 6-DoF simulation environment platform named MAV3DSim.

This paper addresses the problem of designing and experimentally validating a nonlinear robust control to attitude and altitude of a quadrotor unmanned flying vehicle (UAV). First a disturbance observer is proposed, focus on the attitude regulation control problem of a quadrotor in presence of external disturbances based on the angular velocity measurements and the control inputs. The stability analysis of the nonlinear observer scheme is proven via the use of Lyapunov theory. Later, we focus on the altitude dynamics of a quadrotor in the presence of uncertainty like wind gust are presented. A sliding mode control was proposed, the gain of control can be decreased and, as a result, the chattering amplitude is reduced. The objective is to introduce an adaptation in the control law in order to decrease the gain to the minimal value preserving the sliding mode control and keeping his property of a finite-time convergence. Finally, simulation and experimental results in a quadrotor are presented to show the effectiveness of the proposed nonlinear algorithm in presence of external disturbances.

This contribution presents a modeling technique for an aerial manipulator based on a quad-rotor vehicle provided with a robotic arm. Dual quaternions, which are a little explored but powerful mathematical tool, are proposed as an alternative to the classical Euler angles approach for the kinematic and dynamic modeling. A feedback control law based on dual quaternions is used to validate the proposed model, taking into account the external effects of the robotic limb. Numerical simulations and experiments validate the proposal, opening a path for future research.

This paper deals with the real-time stabilization of a Quadrotor mini helicopter applying a discrete optimal control. A discrete control strategy is better adapted to be executed in a micro-controller, therefore better results are expected with respect to continuous case. Furthermore, the optimal control law allows to helicopter to save energy and then increase its time of flight. The discrete optimal control law is synthesized considering an infinite horizon together with an exact linearization of the nonlinear dynamics of flying vehicle. At the end of this procedure the optimal control law obtained through an exact linearization is simple and easier to tune compared to the optimal strategy where the exact linearization is not performed. Taking into account the obtained experimental results, the proposed control technique produces an appropriate stabilization of the mini UAV.

An enhanced robust altitude control scheme that indicates the improved performance than the typical sliding mode technique for a Quad-rotor aircraft vehicle is proposed in this article by including an integral action in the sliding mode control architecture in order to eliminate the steady-state error induced by the boundary layer and achieving asymptotic convergence to the desired altitude with continuous control input. The proposed integral sliding mode controller is chosen to ensure the stability and robustness of overall dynamics during the altitude control at a desired height reference on the z-axis. Furthermore, we propose a Control Lyapunov Function (CLF) via Lyapunov theory in order to construct the robust stabilizing controller and demonstrate the stability of the z-dynamics of our system. A suitable sliding manifold is designed to achieve the control objective. At last, the simulations and experimental studies are supported by different tests to demonstrate the robustness and effectiveness of the proposed enhanced robust altiutde control scheme subject to bounded external disturbances in outdoor environment.

International audience; The present paper addresses the transition stage of a Gun-Launched Micro Air Vehicle (GLMAV) whose main goal is to rapidly position a rotorcraft MAV over a high-risk scene (Prison riots, blind zones: e.g. over-the-hill, etc.). The development of this robotic platform is part of an overall ongoing project (GLMAV) headed by the St. Louis French-German Research Institute (ISL). The vehicle is launched at a distance of 500 m and a height of 100 m, where the GLMAV will collect and transmit visual information from the scene. Issues raising from the use of the gun-based launching technique are discussed in detail. A control strategy is proposed to overcome such problems and to stabilize the GLMAV. High-fidelity simulations, covering ballistic and transition phases, validate the control policy adopted to face the MAV gun-launching problem.

International audience; This paper deals with two nonlinear controllers based on saturation functions with varying parameters, for set-point regulation and trajectory tracking on an Underwater Vehicle. The proposed controllers combine the advantages of robust control and easy tuning in real applications. The stability of the closed-loop system with the proposed nonlinear controllers is proven by Lyapunov arguments. Experimental results for the trajectory tracking control in 2 degrees of freedom, these are the depth and yaw motion of an underwater vehicle, show the performance of the proposed control strategy.

In robotics, the navigation problem can be split in planning, execution, checking and correction. An approach to deal with these tasks is based on the Multi-Layer Control scheme (MLCS). In this technique, each layer is responsible for an individual step of the formation control problem, such as; to define and optimize the desired robot pose; to avoid or minimize collision risks; to control the robots for accomplishing the formation, and so on. In this work, a positioning task for a platoon of six aerial robots is guided by the MLCS methodology. The procedure is developed as follows: first, the off-line planning layer organizes the desired formation according to the current robot position; then, the robots are clustered in a set of triangular formations; and finally, each triangle is controlled for reaching its desired goal. Simulation results illustrate and validate the proposal.

The aim of this paper is to provide a mathematical model for a convertible unmanned aerial vehicle that combines the capabilities of a flying wing and tricopter with tilt rotors. This article presents the mathematical model for airplane and tricopter modes as well as the way they are related during the transition phase. Also is presented a control strategy to hover flying. Finally, it is presented simulation results of tricopter mathematical model under controls developed.

This paper presents a novel autonomous take-off and landing approach which uses a discrete-time finite-horizon suboptimal nonlinear control strategy to achieve a smooth landing on specific colored platform. By color-based tracking we can improve the performance of the position landing by correcting the position given by the GPS. The signal of the GPS is not always reliable since the accuracy strongly depends on the environment situation and the correction by vision servoing is then necessary. Experimental results using the proposed approach show a better performance than those where the GPS signal is only used to perform the take-off and landing tasks in a completely autonomous way in presence of wind gusts.

Inertial Stabilised Platform, better known as gimbal are becoming increasingly popular, with a large range of products now available in mainstream shops. Most of these items are nonetheless controlled using very basic algorithms that do not offer best achievable performances. First, each axis is controlled independently of one another. Then, they make use of trigonometry for their calculation. Lastly, their behaviour depends on the type of payload or on the orientation of this latter. Present paper proposes an advanced control which aims at solving these classic control issues without requiring as much computational power. It is based on quaternion representation and self-adapts to the characteristics of the payload it stabilises. Although only simulation could be performed to check the performances of such control, results look very promising and may help to construct more polyvalent and efficient gimbals which would further facilitate their expansion.

This paper deals with developing an automatic controller that solves the attitude stabilization for a Quadrotor unmanned aerial system (UAS). The controller used a simultaneous strategy of estimation and compensation of uncertainties as well as disturbances. The approach consisted of integrating a neuro-fuzzy system that implemented a set of differential neural networks (DNNs) as consequence section of Takagi-Sugeno (T-S) fuzzy inference. The combination of these two strategies applied on a Quadrotor UAS has the main purpose of forcing a hover flight while the tracking desired angular positions are attained. The control method identified the unknown nonlinearities and bounded external disturbances firstly. This information served to compensate the uncertain section of the Quadrotor dynamics. An additional section in the controller design enforces the stabilization of the tracking error with respect to a given reference trajectory. The control design methodology supported on the Lyapunov stability theory and guaranteed ultimate boundedness of the identification and tracking errors. Academic simulation tests confirmed the superior performance of the proposed algorithm based on the combination of DNNs and T-S techniques.

This paper presents a control strategy for two planar vertical take-off and landing (PVTOL) vehicles cooperating to transport a rigid body load without any explicit exchange of state information between them. This means that the vehicles have only access to their own state variables. The solution and stability analysis is based on a passivity approach.

This paper presents an adaptive PD control law by using a modified MIT rule. The adjustment mechanism of the MIT rule has been implemented with three types of sliding-mode control, i.e., classical sliding-mode control, second order sliding-mode (2-SM), and high order sliding-mode control (HOSM). The proposed controllers have been designed for the directional and lateral dynamics of a fixed-wing mini aerial autonomous vehicle (MAV). Several simulations have been carried out in order to analyze the modified MIT rule.

This paper presents a stability analysis of the interaction between a human and a linear moving Force Augmenting Device (FAD). The analysis employs a mathematical model of the human arm, the FAD and their interaction. As a depart from past works, this article presents a stability analysis considering time-delays in the human model. A key ingredient in the analysis is the use of the Rekasius substitution for replacing the time-delay terms. It is proved that the human machine interaction is stable when the human model has no delays. When delays are considered in the human model, the analysis provides an upper bound for the time-delays preserving a stable interaction. Numerical simulations allow to assess the human-FAD interaction. An experiment is performed with a laboratory prototype, where a human operator lifts a load. It is observed that the human machine interaction is stable and the human operator is able to move the load to a desired position by experiencing very little effort.

Mini underwater vehicles becomes popular and interesting for the control community. Navigate them autonomously, it is a challenge that requires different control approaches to improve performance due to external and unknown perturbations that could be present. Our interest is to propose a robust nonlinear controller to stabilize an underwater robot. The mini submarine used in this work has some mechanical properties that increases its potential to apply it in several applications. Solving this problem requires, in a first time, the development and analysis of its dynamic model in order to design a control law. The control algorithm is based on the backstepping technique with adaptive and integral properties. The stability analysis is proved using Lyapunov functions. Graphs from simulations results introduce the good behavior of the closed-loop system even in presence of unknown and external perturbations. Experimental results confirm the well performance when applying the controller in real time.

Summary This paper addresses the directional control problem of autonomous air vehicles in order to obtain trajectory tracking capabilities when flying in other than calm conditions. The control strategy is designed in the framework of the Lyapunov theory, and adaptive techniques are employed for online wind identification. An application of light fixed-wing unmanned aerial vehicles that consists in tracking straight-line paths between geo-referenced waypoints is first formulated, and the dynamic of the cross track error with respect to such trajectory is further obtained from the lateral airplane equations of motion. The dynamic order of the closed-loop adaptive system is guaranteed to be minimal by choosing the proper variables so that the tuning functions method could be applied. Several simulations taking into account unknown wind have been performed to analyze the behavior and the robustness of the control scheme. Copyright © 2014 John Wiley & Sons, Ltd.

International audience; Despite the substantial interest in UAVs, little attention has been paid to developing realistic simulators which represents a complete mathematical model of the UAV and the external variables, that is the reason why we present a Multi-Aerial Vehicle 3D Simulator (MAV3DSim) that will help with the validation of new controllers. It is multi-aerial because it has the possibility to simulate a fixed-wing or a quadrotor UAV. The multiple display options of the MAV3DSim provides a big help in the development of the controllers. Finally we present the previous implementation of two different controllers, for the fixed-wing a path following strategy is implemented while for the quadrotor an attitude and altitude controller, both strategies are implemented on the same simulation environment.; Malgré l'intérêt substantiel en matière de drones, peu d'attention a été accordée au développement de simulateurs réalistes qui représente un modèle mathématique complète de l'UAV et les variables externes, ce est la raison pour laquelle nous présentons un multi-aérienne 3D Vehicle Simulator (MAV3DSim) qui aidera à la validation de nouveaux contrôleurs. Il est multi-aérienne car il a la possibilité de simuler un aéronefs à voilure fixe ou d'un drone quadrirotor. Les multiples options d'affichage de la MAV3DSim fournit une grande aide dans le développement des contrôleurs. Enfin, nous présentons la mise en œuvre précédente de deux contrôleurs différents, pour la voilure fixe un chemin stratégie suivante est mise en œuvre tandis que pour le quadrirotor un contrôleur de l'attitude et de l'altitude, les deux stratégies sont mises en œuvre sur le même environnement de simulation.

International audience; In this paper the development and practical implementation of a Passivity-Based Control (PBC) algorithm to stabilize an Unmanned Aerial Vehicle (UAV) described with unit quaternions are presented. First, a mathematical model based on Euler-Lagrange formulation using a logarithmic mapping in the quaternion space is introduced. Then, a new methodology: a quaternion-passivity-based control is derived, which does not compute excessive and complex Partial Differential Equations (PDEs) for synthesizing the control law, making a significant advantage in comparison with other methodologies. Therefore, the control design to a system as the quad-rotor is easily solved by the proposed methodology. Another advantage is the possibility to stabilize quad-rotor full dynamics which may not be possible with classical PBC techniques. Experimental results and numerical simulations to validate our proposed scheme are presented.

The design and implementation of a force augmenting exoskeleton for the elbow joint is presented in this paper. The force augmentation comes from electric motors as well as from pneumatic muscles that are the actuators of the device. This is the reason to say that the device is hybrid. Electric motors are more easily and precisely controlled than pneumatic muscles, however the last ones can move heavier weights. The autonomy of a device of this kind is reduced due to the energy expenditure of the two types of actuators employed. For this reason a suboptimal discrete nonlinear control was implemented which improves performance and lengthens considerably the operation time. A dynamical model of the device is also presented and a comparison between a PD+G and a suboptimal control is made. Simulation results are presented.

International audience; In this paper we address the problem of real-time optimal trajectory generation of a micro Air Vehicle (MAV) in unknown and low-sunlight environments. The MAV is required to navigate from an initial and outdoor position to a final position inside of a building. In order to achieve this goal, the MAV must estimate a window of the building. For this purpose, we develop a safe path planning method using the information provided by the GPS and a consumer depth camera. With the aim of developing a safe path planning with obstacle avoidance capabilities, a model predictive control approach is developed, which uses the environment information acquired by the navigation system. The results are tested on simulations and some preliminary experimental results are given. Our system's ability to identify and estimate a window model and the relative position w.r.t. the window is demonstrated through video sequences collected from the experimental platform.

The stability analysis of a vision-based control strategy for a quad rotorcraft UAV is addressed. In the present application, the imaging sensing system provides the required states for performing autonomous navigation missions, however, it introduces latencies and time-delays from the time of capture to the time when measurements are available. To overcome this issue, a hierarchical controller is designed considering a time-scale separation between fast and slow dynamics. The dynamics of the fast-time system are stabilized using classical proportional derivative controllers. Additionally, delay frequency and time domain techniques are explored to design a controller for the slow-time system. Simulations and experimental results consisting on a vision-based road following task are presented.

This paper presents the study of a quadrotor trajectory tracking control for outdoor applications where the measurements provided by the sensors are noisy and imprecise. Time scale separation of the translational and rotational quadrotor dynamics is used to achieve trajectory tracking. A sliding mode controller is proposed for the translational dynamic and provides the desired orientation for the UAV, which is controlled by a linear PD control. Simulations are carried out to test the proposed controller taking into account the measurement error from real not expensive sensors.

5th Symposium on System Structure and Control 11th Workshop on Time-Delay Systems 6th Workshop on Fractional Differentiation and Its Applications; International audience; This paper deals with an experimental comparison between a proportional derivative (PD) controller and an adaptive nonlinear state feedback one, both applied on a tethered autonomous underwater vehicle. The aim is to show the behavior of the closed loop system in the nominal case for each of these two controllers, and then to test their robustness towards some parameters changes. The PD on one hand has a good performance for systems with an unknown model. The adaptive control law on the other hand is known to adjust the unknown parameters of the plant in order to converge to the desired trajectory. This study shows experimental results performed using each of the above mentioned control laws.

A mathematical model that describes the movement of the fingers of the hand is reported in this paper. Electromyographic signals (EMG) are recorded from the forearm and are analyzed to detect which of them are responsible of the movement of each finger. The way the EMG signals are analyzed to determine which of them produce the movement of the fingers is also described. These will be used in an ongoing project that consists of a glove used to enhance the force of the hand of a user.

This article addresses the problem of a real-time implementation trajectory control for a miniature Quad-rotor aircraft along a time-depedent trajectory outdoor. A robust algorithm control based on sliding mode approach is proposed for the trajectory-tracking task, that ensures the convergence to a desired path r(t) in a finite time. A polynomial smooth curve trajectory is selected as reference signal in where the corresponding derivatives of the function are bounded. The proposed solution consists of implementing a real-time control law based on sliding mode using GPS measurements in order to obtain the position in the plane XY to accomplish the desired trajectory. A Lyapunov candidate function is used in order to obtain the control law as well as corresponding stability analysis of the system. Simulation and experimental results of trajectory-tracking control are presented to assess the performance and robustness of the proposed controller in the presence of small perturbations outdoor.

This study describes the design of an output based controller for a 4-DOF (three dimensional position x-y-z as well as yaw angle) Autonomous Underwater Vehicle (AUV) using a mixed structure of a backstepping like control form and a Robust Exact Differentiator (RED). The class of AUV system allowed to control the AUV's vertical coordinate independently. To adjust the x-y plane trajectories, the angular velocity with respect to the z coordinate was used as a virtual control action. The controller was designed to solve the tracking problem of the AUV to a desired reference trajectory. The controller was originally designed under the assumption of using the whole state to construct the closed-loop structure. As the differentiator converged in finite-time, then the controller was adjusted to use the velocity information obtained by the RED. The tracking performance obtained by the proposed controller was evaluated by tracking two reference trajectories. An acceptable performance was obtained by the application of the mixed controller in terms of the mean-square error of tracking problem. A set of simulations with different reference trajectories was used to evaluate the implementation aspects of the solution suggested in this study.

International audience; This paper presents the design and simulation of an energy-based control strategy to stabilize a quadrotor described with unit quaternions and their axis-angle representation. The mathematical model is based on Euler-Lagrange formulation using a logarithmic mapping in the quaternion space. The proposed solution introduces a new approach: a quaternion-energy-based control, which introduces an energy expression defined as a Lyapunov function. The designed control law allows the stabilization of the vehicle in all its states. Simulation results and an experimental validation are presented to corroborate the effectiveness of the proposed strategy.

This paper addresses simulation results about the altitude control of a quad-rotor unmanned flying vehicle (UAV) in the presence of uncertainty like wind gust. A sliding mode control was proposed, the gain of control can be decreased and, as a result, the chattering amplitude is reduced. The objective is to introduce an adaptation in the control law in order to decrease the gain to the minimal value preserving the sliding mode control and keeping his property of a finite-time convergence.

In this paper, a robust altitude control scheme is proposed for a mini-Quadrotor UAV system based on sliding mode controller with an integral action to eliminate the steady-state error induced by the boundary layer in order to achieve asymptotic convergence to the desired altitude with continuous control input. The proposed integral sliding mode controller is chosen to ensure the stability and robustness of overall dynamics during the altitude control at a desired height reference on the z-axis. Furthermore, we propose a Control Lyapunov Function (CLF) via Lyapunov theory in order to construct the robust stabilizing controller and demonstrate the stability of the z-dynamics of our system. A suitable sliding manifold is designed to achieve the control objective. At last, the theoretical results are supported by different simulation tests to verify the robustness and effectiveness of proposed robust control scheme in presence of bounded external disturbances.

This paper addresses the problem of autonomous navigation of a quadrotor helicopter using state estimators when the GPS signal is not available. The main objective is to estimate the translational position and velocity of the flying machine. The observer proposed uses a double integral approximation of the acceleration defined in the mathematical model in order to estimate the states previously mentioned. To apply this approach, a recursive least squares algorithm is programmed to get better estimations. Real-time experiments have been conducted in order to verify the validity and effectiveness of the proposed estimation approach, and the obtained results are presented and discussed.

“Field Oriented Control” (FOC) is the the most efficient way to control a bruchless motor. This control generates constantly a magnetic field perpendicular to the rotor, which maximises its efficiency. However, to do so, it requires knowledge of the rotor position in real time. The latter can be measured using additional sensors which can be problematic for many reasons. Alternatively, the so-called “sensorless” control consists in the analysis of the electric motor response but needs to know certain characteristics of the engine, compromising compatibility. In this paper, we propose an adaptive control based on the hypothetical rotor position method, which overcomes these problems. This control has also the advantage of remaining optimal although the motor parameters vary over time due to external conditions (e.g. temperature) or aging. The results obtained are very promising and seem to prove its suitability for implementation in real applications.

This paper presents the modeling, the design of control laws, for Euler angles and altitude, and their implementation. The proposed controller is based on the backstepping procedure and uses a state feedback linearizing technique to guarantee tracking of the desired Euler angles and altitude on the ornithopter. The provided controller provides exponential convergence to the desired values. Numerical and experimental applications of the proposed algorithm illustrates the performance of the control technique.

International audience; This work presents the modeling and control of an aerial manipulator based on a quadrotor with a robotic arm using the dual quaternion approach. First the kinematic model of the complete system is obtained using dual quaternions to represent multiple rotations and translations, then the dynamic model is developed via the Newton-Euler formalism. A position control law is used to stabilize the vehicle around a desired position and orientation using a smooth trajectory. The closed-loop system is then numerically simulated to corroborate stability. In addition, experimental flight tests were performed for validation.

The UAVs business experiences currently a strong growth in particular thanks to the popularisation of its mini class (e.g. DJI Phantom, Parrot Bebop…). Nevertheless, there is still a need for more capable aircraft, mainly in terms of payload and endurance, in both military and civilian markets. This type of aircraft is historically known as the tactical class, which is a compromise between the affordability of the mini class and the capacity of MALE class. It was paradoxically the first class to be developed, long before common drones started to be sold in department stores. Contrary to the mini class drones, which are mostly hand operated, tactical aircraft face the main issue of requiring an airfield for take-off and sometimes for landing, when not using a parachute. Such a problem could be solved by providing the drones with a STOL (Short Take-Off Mass) capacity or even better a VTOL (Vertical Take-Off and Landing Mass) ability. The former is partially proposed by most models present in the market by using most of the time external systems (e.g. Flight deck, catapult, ramp…). However, although there have been several attempts to provide the later, using often a helicopter configuration, resulting aircraft have not achieved the performances of classical aeroplanes. This article introduces a new configuration of VTOL aircraft, particularly well adapted to heavy UAVs. A general sizing is carried out in order to meet typical performances required by the tactical class. Even if only the results of the conceptual design are available for now, the VTOL capacity of the drone seems to be obtained with negligible impacts to its overall performance, which is comparable to fixed-wing drones.

The design and testing of unmanned aerial vehicles is a difficult task due to the high risk of damage to property during testing, to prevent accidents from happening it is indeed necessary to perform extensive simulation of controllers to ensure good stability and performance. We have been working to solve this problem by developing a realistic simulator by using a complete mathematical model of the UAV including the external variables, so we present a Multi-Aerial Vehicle 3D Simulator (MAV3DSim) that will help to the validation and verification of new controllers in a safety way. It is multi-aerial because it has the possibility to simulate a variety of types of UAVs. The multiple display options of the MAV3DSim has been proven a significant help in the development of the controllers. A hardware in the loop (HIL) implementation is used in combination with the autopilot hardware used in the experimental platform.

This paper addresses the problem of enabling Unmanned Aircraft Systems (UAS) to avoid mid-air collisions during path planning applications. We propose an improved strategy that allows the UAS to negotiate obstacles encountered during flight, while keeping the objective of finding a feasible path towards its destination. Our method computes multiple steps along the UAS's path based on GPS coordinates, a strategy which we refer to as dynamic waypoints generation. When a risk of collision is encountered, new dynamic waypoints are generated by taking into account the obstacle's planar coordinates, as well as an approximate circular envelope around it, which allows addressing a most type of obstacle's shapes. Real-time experiments performed outdoors with a holonomic UAS are provided, demonstrating the effectiveness and reliability of the proposed strategy.

This paper presents the problem of safe and fast transportation of packages by an Unmanned Aerial Vehicle (UAV) kind quadrotor. A mathematical model and a control strategy for a special class of underactuated mechanical systems, composed of a quadrotor transporting a cable-suspended payload, are proposed. The Euler-Lagrange formulation is used to obtain the dynamic model of the system, where the integrated dynamics of the quadrotor, cable and payload are considered. An Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) is chosen because of its inherent robustness against parametric uncertainty and unmodeled dynamics. Two cases are considered to obtain two different control laws, in the first case, the designed control law depends on the swing angle of the payload, in the second case the control law does not depend on it. The control objective is to transport the payload from point to point, with swing reduction along trajectory. Experimental results using monocular vision based navigation are shown to evaluate the proposed control law.

An unmanned aerial vehicle (UAV) stabilization strategy based on computer vision and switching controllers is proposed. The main goal of this system is to perform tracking of a moving target on ground. The architecture implemented consists of a quadrotor equipped with an embedded camera which provides real-time video to a computer vision algorithm where images are processed. A vision-based estimator is proposed, which makes use of 2-dimensional images to compute the relative 3-dimensional position and translational velocity of the UAV with respect to the target. The proposed estimator provides the required states measurements to a micro-controller for stabilizing the vehicle during flight. The control strategy consists of switching controllers, which allows making decisions when the target is lost temporarily or when it is out of the camera's field of view. Real time experiments are presented to demonstrate the performance of the target-tracking system proposed.

The present paper addresses the transition stage of a Gun-Launched Micro Air Vehicle (GLMAV) whose main goal is to rapidly position a rotorcraft MAV over a high-risk scene (Prison riots, blind zones: e.g. over-the-hill, etc.). The development of this robotic platform is part of an overall ongoing project (GLMAV) headed by the St. Louis French-German Research Institute (ISL). The vehicle is launched at a distance of 500 m and a height of 100 m, where the GLMAV will collect and transmit visual information from the scene. Issues raising from the use of the gun-based launching technique are discussed in detail. A control strategy is proposed to overcome such problems and to stabilize the GLMAV. High-fidelity simulations, covering ballistic and transition phases, validate the control policy adopted to face the MAV gun-launching problem.

The paper addresses the flight control of a quad-rotor subject to two dimensional unknown static/varying wind disturbances. A model separation is proposed to simplify the control of the six-degrees-of-freedom (6DOF) nonlinear dynamics of the flying robot. Such approach allows to deal with quad-rotor's 3D-motion via two subsystems: dynamic (altitude and MAV-relative forward velocity) and kinematic (nonholonomic-like navigation) subsystems. In terms of control, a hierarchical control is used as the overall control structure to stabilize the kinematic underactuaded subsystem. A control strategy based on sliding-mode and adaptive control techniques is proposed to deal with slow and fast time-varying wind conditions, respectively. This choice not only provides well tracking control but also improves the estimation of unknown disturbance. The backstepping technique is used to stabilize the inner-loop heading dynamics, such recursive design takes into account a constrained heading rate. Promising simulations results show the validity of the proposed control strategy while tracking a time-parameterized straight-line and sinusoidal trajectory.

SUMMARYIn this paper we address the problem of stabilization and local positioning of a four-rotor rotorcraft using computer vision. Our approaches to estimate the orientation and position of the rotorcraft combine the measurements from an Inertial Measurement Unit (IMU) and a vision system composed of a single camera. In the first stage, the vision system is used to estimate the position and yaw angle of the rotorcraft, while in the second stage the vision system is used to estimate the translational velocity of the flying robot. In both cases the IMU gives the pitch and roll angles at a higher rate. The technique used to estimate the position of the rotorcraft in the first stage combines the homogeneous transformation approach for the camera calibration process with the plane-based pose method for estimating the position. In the second stage, a navigation system using the optical flow is also developed to estimate the translational velocity of the aircraft. We present real-time experiments of stabilization and location of a four-rotor rotorcraft.

The paper presents initial results towards a reactive vision-based autonomous navigation within an indoor corridor performed by a quad-rotor miniature air vehicle (MAV). A model separation is proposed to simplify the control of the six-degrees-of-freedom (6DOF) dynamics of the flying robot. Such approach allows to deal with quad-rotor's 3D-motion through two subsystems: dynamic (altitude and MAV-relative forward velocity) and kinematic (nonholonomic navigation) subsystems. In terms of control, a hierarchical control scheme is used to stabilize dynamic and kinematic underactuaded subsystem involved in the navigation task. A Lyapunov-based bounded controller is used to stabilize the angular error dynamics. Furthermore, the corresponding stability analysis is presented to guarantee the asymptotical convergence of angular states to the origin. Promising simulations results shows the validity of the proposed control strategy since experimental values obtained from semi-automatic flight of quadrotor while navigating through an indoor corridor were used in such numerical evaluation.

This paper addresses the problem of quadrotor flight formation control. The quadrotor simplified dynamics is represented by integrators in cascade. A system transformation is presented that reduces the input-output behavior of a chain of integrators into a single integrator. Therefore, the standard coordination control algorithms can be directly applied. A second strategy is proposed consisting in transforming the chain of integrators into a strictly positive real (SPR) system and then an algorithm is proposed for the formation control of SPR systems. The proposed algorithm is illustrated in simulation.

International audience; This paper presents a wind power system based on a kite attached with a rope to a dynamo on the ground. We present the aerodynamical equations which model the system and propose a control strategy for stabilizing the angle of flight and the length of the rope. The control objective is to keep the angle of the rope fixed to a desired value during an energy producing cycle in which the rope length follows a sinusoidal trajectory. The control strategy is based on the feedback linearization technique. The proposed control law is first tested in numerical simulations. An experiment has been set up including a wind tunnel, a wing and various sensors. The control strategy has been successfully tested in the experimental set up.

This work presents the development of a mini underwater vehicle ( Triton-PR ), the embedded system, and the experiments in real-time for autonomous hover operation. Artificial vision allows the vehicle to obtain the translational position and velocity. The main characteristic of the embedded system is the implementation of low cost devices and materials, besides the number and location of the thrusters was chosen in order to have enough power and generate the rotation and translation movements. The dynamical model of the ( Triton-PR ) is described by the classic Euler-Lagrange equations, and a PD controller based on saturation functions is proposed for providing autonomous attitude and position of the robot. Finally, the performance of the vehicle is shown in simulation and real-time experimental results.

In the present work a mathematical model and a control methodology for a special class of underactuated mechanical system, composed by an Unmanned Aerial Vehicle (UAV) kind quadrotor transporting a cable-suspended payload, is proposed. The Euler-Lagrange formulation is used to derive the dynamic model of the system, where the integrated dynamics of the quadrotor, cable and payload are considered. An Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) for a quadrotor UAV transporting a cable-suspended payload is developed. The control law designed does not depend on the swing angle of the cable. The control objective is to transport the payload from point to point, with swing suppression along trajectory. Experimental results are shown to evaluate the proposed control law.