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International audience; Two novel nonlinear control schemes for Unmanned Aerial Vehicles (UAV) carrying a load and their comparative results are presented in this paper. The goal is to carry the load to a desired position, with oscillation attenuation along the trajectory. The proposed control structures are hierarchical schemes consisting of nonlinear controllers to stabilize the vehicle translational movements and the payload swing together with a well-known state-dependent differential Riccati equation controller to stabilize the rotational dynamics. We present new methodologies where two nonlinear controllers are proposed to obtain precise aerial vehicle positioning and efficient load oscillation reduction by exploiting the natural coupling between the horizontal quadcopter movement and the payload oscillation. It is shown that asymptotic stability can be guaranteed by the use of the Lyapunov approach and La Salle’s invariance principle. Numerical experiments were carried out to validate the nonlinear control behaviors where the results show improvements with respect to a strategy from the literature.

In this brief, the implementation of a suboptimal nonlinear discrete control to optimize the energy consumption in a hybrid exoskeleton for the elbow joint is presented. The exoskeleton is used to amplify the strength of the user and is hybrid in the sense that it combines two types of actuators: pneumatic muscles and Harmonic Drive motors, which give power and precision to the system, respectively. The exoskeleton is autonomous in the energetic sense, and it is driven by compressed air and batteries. The suboptimal control is used to increase the operation time of the exoskeleton. This control law penalizes the energy consumption, and it has a direct effect on the operation time of the prototype.

Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low computational cost. In this paper, the objective is to establish performance–guaranteed emotional learning–inspired control (ELIC) strategies for autonomous multi–agent systems (MAS), where each agent incorporates an ELIC structure to support the consensus controller. The objective of each ELIC structure is to identify and compensate model differences between the theoretical assumptions taken into account when tuning the consensus protocol, and the real conditions encountered in the real system to be stabilized. Stability of the closed-loop MAS is demonstrated using a Lyapunov analysis. Simulation results based on the consensus task of a group of inverted pendulums demonstrate the effectiveness of the proposed ELIC for stabilization of nonlinear MAS.

In this work, the analysis of the dynamic general model of an unmanned underwater vehicle (UUV) based on dual quaternions is presented, then the general dynamic model is reduced to a specific vehicle of 4 DoF, this model eliminates the singularities that exist with the representation of the Euler angle and that the model is more compact than others proposed in the literature [1],[2]. To demonstrate the applicability of the model, three controller strategies are proposed for tracking a trajectory, the first controller is a PD + G, under unknown disturbances it produces a considerable tracking error, the second is an adaptive controller that estimates unknown hydrodynamic parameters, and the third is a robust controller for unknown disturbances and parameter uncertainties. The closed-loop system stability analysis for each controller is based on Lyapunov’s theory, a set of numerical simulations is performedto show the behavior of the vehicle with the proposed controllers. The efficiency of the controllers is shown in Table 2 where it is deduced that the adaptive controller has a better performance. The graphics show that the robust controller has little error tracking and the computational cost is lower.

An energy reduction strategy for a fixed-wing drone with classic configuration is presented in this paper. The strategy is developed using the longitudinal non-linear motion equations of the aircraft, considering the stall effects in the determination of lift and drag forces. Our strategy imposes the aircraft to track a special trajectory allowing the vehicle to perform a curve in ascend, acting against the gravity force. As a consequence of this tracking, the angle of attack of the vehicle is increased arriving to critical values that need to be compensated for avoiding the crash of the vehicle. Therefore, a strategy to avoid the stall stage and recovering the flight stability in the vehicle is proposed. The strategy is evaluated in simulations for validating the performance of the whole system.

The problem of controlling Unmanned Aerial Vehicles (UAV) can be simplified in some cases by designing a controller for the Vertical Take-off and Landing (PVTOL) platform and adapting it to other v...

International audience; This paper presents a hybrid adaptive approximation-based control (HAAC) strategy for a class of uncertain robotic joints' system. The proposed control structure consists of a robust sliding mode controller and an adaptive approximation-based controller. The robust sliding mode controller is designed by using the super-twisting algorithm, which is a particularly effective method to decrease the chattering caused by the traditional sliding mode control (SMC) and compensate the disturbances. Another improvement of the robust sliding mode controller is that the robust control parameters only subject to the upper bound of the derivative of the external disturbances, rather than choosing a relatively large value. Moreover, the designed adaptive approximation-based controller has the following two distinctive features: 1) the control parameters are designed to be adjusted in real time and 2) the prior knowledge of actual robotic model is not required to be known. These features contribute to compensating the uncertainties. The stability of the closed-loop system is proved by using the Lyapunov theory, and the simulation results demonstrate the effectiveness of the proposed control method. Finally, the proposed HAAC could apply in the experiments of industrial robotic joints' system.

International audience; This paper presents a control strategy named auxiliary surfaces sliding mode control (AS-SMC) by using Positive Invariant Set (PIS) to control a class of continuous nonlinear systems with state constraints. The PIS can be regarded as a special kind of sliding surface, and its invariance ensures that the system state can satisfy the constraints in the convergence process. The stability analysis and a PIS theory proof are given. The control strategy is successfully tested in numerical simulations and even effectively applied to the coaxial unmanned helicopter flight control system on hardware in the loop (HIL) platform. The results verify the effectiveness of the proposed control strategy for the experimental set-up.

International audience

SUMMARYA novel underwater vehicle configuration with an operating principle as the Sepiida animal is presented and developed in this paper. The mathematical equations describing the movements of the vehicle are obtained using the Newton–Euler approach. An analysis of the dynamic model is done for control purposes. A prototype and its embedded system are developed for validating analytically and experimentally the proposed mathematical representation. A real-time characterization of one mass is done to relate the pitch angle with the radio of displacement of the mass. In addition, first validation of the closed-loop system is done using a linear controller.

Disturbance rejection is a major concern nowadays for the development of autonomous aerial vehicles technology. In this way, in the control community, the researchers propose complex and robust nonlinear controllers that are in several cases so difficult to be applied in real time. In this paper, a robust linear control scheme for nonlinear aerial system is proposed. The scheme is based on the structural properties of the system such as parametric uncertainties and external disturbances. The control scheme is validated experimentally in real time to corroborate their properties on disturbance rejection. Experimental results illustrate the easy implementation and feasibility of the proposed scheme when the vehicle faces three different scenarios; wind-gust disturbance, variable mass and motor failure. In addition, the scheme presents high efficiency in disturbance rejection, smoother convergence to the desired reference and a low computational demand.

International audience; DC motor speed synchronization is a critical problem in industrial and robotic applications. To tackle this problem, we propose to use a multi-agent consensus-based control scheme that guarantees the convergence of the DC motor speeds to either fixed or time-varying reference. A detailed robustness analysis considering parametric uncertainty and time delay in the multi-agent system is performed to guarantee the consensus on the speed of DC motors in actual practice. The results obtained concerning the robustness analysis allowed us to implement experimental tests on a three-motor system using a wireless communication system to achieve satisfactory performance

International audience

This research work focuses on the design of a robust-adaptive control algorithm for a 4DOF Unmanned Underwater Vehicle (UUV). The proposed strategy is based in a Non-Singular Terminal Sliding Mode Control (NTSMC) with adaptive gains, where the proposed adaptation mechanism ensures that the gains remain bounded. In this control strategy a non-singular terminal sliding surface is proposed to obtain a faster convergence of the tracking errors. The NTSMC ensures Practical Finite-Time Stability for the closed-loop system as well as exhibits a chattering reduction. In order to demonstrate the satisfactory performance of the proposed controller, a set of experiments was performed with a Non-Singular Terminal Sliding Mode Controller and an Adaptive Non-Singular Terminal Sliding Mode Control (ANTSMC) in real time for trajectory tracking in the X-Y plane, the graphs showed that the ANTSMC converges faster to a smaller region and reduces oscillations.

Control theory applied to multirotor aerial systems (MAS) has gained attention with the recent increase on the power computation for embedded systems. These systems are now able to perform the calculations needed for a variety of control techniques, with lower cost of sensors and actuators. These types of control algorithms are applied to the position and the attitude of MAS. In this paper, a brief overview evaluation of popular control algorithms for multirotor aerial systems, especially for VTOL - Vertical Take-Off and Landing aircraft, is presented. The main objective is to provide a unified and accessible analysis, placing the classical model of the VTOL vehicle and the studied control methods into a proper context. In addition, to provide the basis for beginner users working in aerial vehicles. In addition, this work contributes in presenting a comprehensive analysis of the implementation for the Nonlinear and Linear Backstepping, Nested Saturation and the Hyperbolic Bounded Controllers. These techniques are selected and compared to evaluate the performance of the aircraft, by simulations and experimental studies.

SUMMARYSafe and accurate navigation for autonomous trajectory tracking of quadrotors using monocular vision is addressed in this paper. A second order Sliding Mode (2-SM) control algorithm is used to track desired trajectories, providing robustness against model uncertainties and external perturbations. The time-scale separation of the translational and rotational dynamics allows to design position controllers by giving a desired reference in roll and pitch angles, which is suitable for practical validation in quad-rotors equipped with an internal attitude controller. A Lyapunov based analysis proved the closed-loop stability of the system despite the presence of unknown external perturbations. Monocular vision fused with inertial measurements are used to estimate the vehicle's pose with respect to unstructured scenes. In addition, the distance to potential collisions is detected and computed using the sparse depth map coming also from the vision algorithm. The proposed strategy is successfully tested in real-time experiments, using a low-cost commercial quadrotor.

Wind is considered a strong disturbance for quadrotor aircrafts (UAV) when an outdoor task at a fixed point is carried out. The effect of wind produces a distortion on the attitude of the vehicle which is reflected on undesired longitudinal movements. This paper addresses a real-time implementation and design of a robust embedded control-observer based on a type high-gain observer algorithm for on-line estimation and compensation of external disturbances produced by wind gusts on an autonomous quadrotor aircraft. A real-time experimental implementation of embedded Residual High Gain algorithm control is proposed in order to eliminate the effects of real perturbations in the hover position of the UAV. A Lyapunov function was used to practical stability analysis the system. Also numerical simulations were carried out to estimate wind behavior by the use of Drydel mathematical wind model. The main contribution of this work is the implementation of a Residual High Gain Observer in an outdoor real-time experiment in presence of real wind gusts perturbations. The proposed embedded algorithm control improves the stabilization of an UAV in the presence of real wind gusts with average of 8 m/s. The proposed algorithm improved the UAV behavior as shown by the GPS position experimental results, decreasing the wind effect on the translational movement of the aircraft.

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.

Conventional control strategies for holonomic Unmanned Aircraft Systems (UASs) require that, while executing a mission, the UAS attitude dynamics remains very close to zero in order to satisfy the assumption of small angles approximation. This requirement may be valid for hover flight, but not for translational flights or aggressive maneuvers. To overcome this issue, this paper presents the controllability analysis for a non-linear representation of a holonomic UAS. Under the proposed scheme, it is shown that it is possible to design control schemes for stabilizing the complete UAS state space without the necessity of separating the system in attitude and translation subsystems. A set of simulations are presented to evaluate the effectiveness of the proposed control laws. These results show that the proposed strategy enables the UAS to track a desired trajectory while keeping the attitude close to a desired value.

This paper proposes a simple flying rotor prototype composed of two small airplanes attached to each other with a rigid rod so that they can rotate around themselves. The prototype is intended to perform hover flights with more autonomy than existing classic helicopters or quad-rotors. Given that the two airplanes can fly apart from each other, the induced flow which normally appears in rotorcrafts will be significantly reduced. The issue that is addressed in the paper is how this flying rotor prototype can be modeled and controlled. A model of the prototype is obtained by computing the kinetic and potential energies and applying the Euler Lagrange equations. Furthermore, in order to simplify the equations, it has been considered that the yaw angular displacement evolves much faster than the other variables. Furthermore a study is presented to virtually create a swashplate which is a central mechanism in helicopters. Such virtual swashplate is created by introducing a sinusoidal control on the airplanes’ elevators. The torque amplitude will be proportional to the sinusoidal amplitude and the direction will be determined by the phase of the sinusoidal. A simple nonlinear control algorithm is proposed and its performance is tested in numerical simulations.

This research work focuses on the design of a robust control algorithm for 3D trajectory tracking of a 4DOF Unmanned Underwater Vehicle (UUV). The proposed strategy is based on a combination of the integral sliding mode control technique with the super-twisting controller, guaranteeing a continuous compensation of bounded disturbances and accomplishing a significant reduction on the chattering phenomenon. In order to verify stability of the closed-loop system, Lyapunov theory is used to guarantee the asymptotic stability in the tracking errors. To demonstrate the satisfactory performance of the proposed controller even in presence of disturbances, a set of simulations and real-time experiments were performed for the trajectory tracking. The graphs show that the proposed controller guarantees the converges to the desired references and a high reduction in the chattering effect on the inputs control.

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 presents the control of a quadrotor with a cable-suspended payload. The proposed control structure is a hierarchical scheme consisting of an energy-based control (EBC) to stabilize the vehicle translational dynamics and to attenuate the payload oscillation, together with a nonlinear state feedback controller based on an linear matrix inequality (LMI) to control the quadrotor rotational dynamics. The payload swing control is based on an energy approach and the passivity properties of the system&rsquo, s translational dynamics. The main advantage of the proposed EBC strategy is that it does not require excessive computations and complex partial differential equations (PDEs) for implementing the control algorithm. We present a new methodology for using an LMI to synthesize the controller gains for Lipschitz nonlinear systems with larger Lipschitz constants than other classical techniques based on LMIs. This theoretical approach is applied to the quadrotor rotational dynamics. Stability proofs based on the Lyapunov theory for the controller design are presented. The designed control scheme allows for the stabilization of the system in all its states for the three-dimensional case. Numerical simulations demonstrating the effectiveness of the controller are provided.

In this paper, a teleoperation system for a quadrotor using a virtual environment is presented. A virtual aerial vehicle was introduced by applying the dynamic model of a quadrotor. An attitude controller was implemented for an operator to pilot the drone. The behavior of the virtual drone is communicated to a real vehicle through a mapping between the real and virtual spaces. This mapping is introduced in a robust quaternion-based controller ensures a safe flight in the real world. Simulations and experimental results are carried out to validate the proposal. With this idea of controlling a drone virtually, the performance of beginner and expert drone pilots is improved.

In this article, the mathematical model based on quaternions for an underwater autonomous vehicle (AUV) of 6 DOF is developed, to avoid singularities that appear in the representation of Euler's angles. For this vehicle, a Non-Singular Fast Terminal Sliding Mode Control (NFTSMC) non-linear controller is proposed, which presents a variation in the sliding surface that guarantees a high rate of convergence of the states in finite time. To verify the stability of the closed-loop control system, an approach of the Lyapunov theory is used, ensuring the convergence in finite time of the tracking errors to a bounded region in the presence of model uncertainties and disturbances. Simulations results are presented to illustrate the efficiency of the developed strategy.

In this paper a real-time approach for human bodies detection at outdoors environments by using thermal images taken from an Unmanned Aerial System (UAS) is presented. The first step of the proposed algorithm consist on the extraction of the thermal signature of human bodies. After that, we used the Moments Representation technique as a shape descriptor to identify human presence in a scene. Finally, a robust controller is developed to enable the multi-rotor vehicle to track a desired reference in order to scan a region of interest. To show the effectiveness of the developed algorithm when it is implemented on an octorotor vehicle, a set of real-time experimental test were conducted and we present the obtained results.

This chapter is devoted to investigate how the dissipativity properties of the various systems examined in the foregoing chapter can be used to design stable and robust feedback controllers (in continuous and discrete time). We start with a classical result of mechanics, which actually is the basis of Lyapunov stability and Lyapunov functions theory. The interest of this result is that its proof hinges on important stability analysis tools, and allows one to make a clear connection between Lyapunov stability and dissipativity theory. The next section is a brief survey on passivity-based control methods, a topic that has been the object of numerous publications. Then, we go on with the Lagrange–Dirichlet Theorem, state-feedback and position-feedback control for rigid-joint–rigid-link systems, set-valued robust control for rigid-joint–rigid-link fully actuated Lagrangian systems, state and output feedback for flexible-joint–rigid-link manipulators, with and without actuators dynamics, and constrained Lagrangian systems. Regulation and trajectory tracking problems, smooth and nonsmooth dynamical systems, are treated. The chapter ends with a presentation of state observers design for a class of differential inclusions represented by set-valued Lur’e systems.

This paper deals with the problem of enabling a team of two Unmanned Aircraft Systems to perform an autonomous load transportation task. We propose a strategy whose main objective is to ensure a stable flight of the team of agents when cooperatively transporting the load. The strategy is based on the implementation of a neural network controller and a neural network estimator, using wavelet activation functions in combination with a cooperative multi-agent control approach. To show the effectiveness and applicability of the proposed framework, a real time experimental implementation is presented. Additionally, a comparison with respect to a classic control law is also provided, demonstrating the superior performance attained when adopting the proposed controller.

This paper presents the pitching moment stability analysis and adjustment for tilt-wing unmanned aerial vehicle (UAV) in hovering flight and vertical take-off and landing (VTOL). The tilt-wing UAVs combine the features of fixed-wing UAVs with VTOL capabilities by tilting the wing and rotor system for the transition between flight modes. Due to its hybrid configuration, the altitude control study, position and attitude, poses a major problem during the entire flight for a given mission. Namely, in the first flight phase the pitching moment could present instabilities with different disturbances, such as wind, that are difficult to compensate. In this paper this problem is analyzed and possible solutions for the stabilization are presented and evaluated in a test bench. These solutions were implemented in new test prototypes demonstrating satisfactory results in outdoor flight tests.

This letter studies the problem of autonomous navigation for unmanned underwater vehicles, using computer vision for localization. Parallel tracking and mapping is employed to localize the vehicle with respect to a visual map, using a single camera, whereas an extended Kalman filter (EKF) is used to fuse the visual information with data from an inertial measurement unit, in order to recover the scale of the map and improve the pose estimation. A proportional integral derivative controller controller with compensation of the restoring forces is proposed to accomplish trajectory tracking, where a pressure sensor and a magnetometer provide feedback for depth control and yaw, respectively, while the remaining states are provided by the EKF. Real-time experiments are presented to validate the navigation strategy, using a commercial remotely operated vehicle (ROV), the BlueROV2, which was adapted to perform as an autonomous underwater vehicle with the help of the robot operative system.

This paper proposes a new high gain observer for a class of non-uniformly observable nonlinear systems with coupled structure driven by sampled outputs. The considered class of systems is p...

Precision trajectory tracking problem for Unmanned Aerial Systems (UAS) is addressed in this work. A novel algorithm that combines a Nonsingular Modified Super-Twisting Controller with a High Order Sliding Mode Observer to enable an aerial vehicle tracking a desired trajectory under the assumption that i) its translational velocities are not available and ii) there are unmodeled dynamics and external disturbances. The proposed Sliding Mode Controller is based on a nonlinear sliding mode surface that ensures that the position and velocity tracking errors of all system’s state variables converge to zero in finite time. Moreover, the proposed controller generates a continuous control signal eliminating the chattering phenomenon. Finally, simulation results and an extensive set of experiments are presented in order to illustrate the robustness and effectiveness of the proposed control strategy.

The back pain is the most common injury in human activities where heavy objects must be lifted or must be suspended for a long time. A weight lifting exoskeleton also known as force augmentation exoskeleton is designed to reduce the strain on the back and the limbs and reduce the risk to suffer injuries. On the other hand, different kinds of controllers have been implemented to achieve whit this goal, for example, a conventional PD Control, PD Control with Gravity Compensation, PD Control with Adaptive Desired Gravity Compensation and PD Control with Robust Compensator. This paper aims to evaluate and compare the performance from the previously cited controllers used to reduce the strain in the back, through the implementation of each controller in a three Degrees Of Freedom (DOF) exoskeleton powered by pneumatic muscle actuators; some numerical simulations as well as experimental trials have been conducted and three different performance indices were used in order to determine the effectiveness of each one with respect to the simple PD controller when the mass to be lifted is unknown.

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.

In this paper, a Nonsingular Fast Terminal Sliding Mode Control (RNFTSMC) is proposed to regulate the position of a mobile lower limb exoskeleton powered by linear actuators with four degrees of freedom. The developed lower limb exoskeleton has the purpose to assist the sit-to-stand and stand-to-sit tasks for people with spinal cord injury (SCI) or elderly people. Currently most of the developed lower limb exoskeletons are dealing with the presence of uncertainties (unmodeled dynamics) and external disturbances (mass changes, opposite forces), caused by the high complexity of the human limbs dynamics. The RNFTSMC has the purpose of dealing with these uncertainties, ensuring a rapid convergence in finite time to the desired position, and reducing the chattering effect produced by the nature of the controller actuators. The human intention movements have been detected using an sEMG signal classifier performed by the Myo Armband device and processed to activate the preprogrammed routines in the RNFTSMC. The desired paths for the knee and hip exoskeleton joints were obtained by recording data from a volunteer who rises from a chair and sat on it, using a motion capture system. To evaluate the effectiveness of the proposed control scheme, real-time experiments under three different scenarios have been carried out.

The design of a robust controller for tracking a depth trajectory of an underwater vehicle in presence of unknown perturbations and uncertainties in the physical parameters of the model is presented in this work. The submarine robot used has properties that were analyzed for the development of the dynamic model and the controller. The control strategy developed is based on a PD controller and a second order filter, which adds robustness to the closed loop system. The control strategy has been successfully tested in real-time experiments, and comparisons with respect to a classic PD controller shown that the controller designed presents superior performance.

In this paper, the use of a class of robust control technique as a tool to compute the robustness margin for a closed loop multi-agent system is discussed. Our approach is based on a leader/follower structure of the multiple robot systems. It is shown that, for multiple agent system with cyclic, chain and balanced topology of information exchange, the result is achieved. A Lyapunov based robust control design for coordination and trajectory tracking of multiple agent systems with parametric uncertainty is presented. The results are illustrated with examples and simulations.

The conventional adaptive control algorithm has a very high real-time requirement for six degrees-of-freedom (DOF) series robotic manipulator system. When the unknown parameters of the robotic manipulator are mutated, it is difficult to ensure the stability of the robotic manipulator system. Aiming at this phenomenon, an optimal algorithm based on adaptive robust control is proposed. When the algorithm is applied to the robotic manipulator system, the actual trajectory at the end of the manipulator is as close as possible to the desired trajectory in the simulation. The algorithm is based on the conventional algorithm, the design of the sliding mode surface to reduce the system position error, adding robust control algorithm to compensate for the instability of the system. The simulation results show that the actual trajectory can quickly track the desired trajectory, and the position error approaches zero.nbsp

This paper presents an adaptive PD control law by using a modified MIT rule. The adaptation of the controller gains is based on the adjustment mechanism of the MIT rule by the gradient method with three types of sliding-mode control, i.e., first order sliding-mode control, second order sliding-mode (2SM), and high order sliding-mode control (HOSM). The proposed adjustment mechanism with the PD controller have been designed for the altitude movement, directional and lateral dynamics of a fixed-wing miniture aerial autonomous vehicle (MAV). Several simulations have been carried out in order to analyze the response of the modified MIT rule.

A robust control scheme for aerial path generation and tracking is proposed in this paper. The control structure is based on the MPC - Model Predictive Control- and the UDE -Uncertainty and Disturbance Estimator - approaches. Both algorithms can be used with simple controllers for becoming more robust with respect to nonlinear uncertainties and external disturbances. The proposed scheme is applied to a quadcopter vehicle. Experimental results confirm the well performance of the closed-loop system when tracking trajectories, even in the presence of perturbations.

This work presents a low level control architecture that allows to handle an aircraft with focus on takeoff and landing maneuvers for fixed wing UAV. The architecture consists of an attitude and angle rate control, on ground course angle control, airspeed control as well as auxiliar stages that allow to determine the required attitude to track the desired course and path angle to follow a desired vertical velocity. These controllers are combined in different forms depending on the phase of takeoff or landing maneuver. By means of simulation the performance of this architecture was illustrated during takeoff and landing maneuvers.

This paper outlines the conception, modeling and control of a rover type modular mini submarine. The development and implementation of the mechanical structure as well as the embedded electronics is described. The onboard instrumentation and sensors required to collect data on the environment and on its own position and orientation are also described. The mathematical representation to describe the movement of an underwater vehicle is analyzed considering the characteristics and limitations of the underwater robot. Furthermore, a control algorithm is implemented based on Lyapunov theory and Backstepping Integral Adaptive (BIA). This control strategy stabilizes the vehicle in position and orientation. The proposed control algorithm is validated in numerical simulations as well as in experimental tests which confirm the good performance of the prototype and the controller.

International audience

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.