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This paper presents an upper limb exoskeleton that allows cognitive (through electromyography signals) and physical user interaction (through load cells sensors) for passive and active exercises that can activate neuroplasticity in the rehabilitation process of people who suffer from a neurological injury. For the exoskeleton to be easily accepted by patients who suffer from a neurological injury, we used the ISO9241-210:2010 as a methodology design process. As the first steps of the design process, design requirements were collected from previous usability tests and literature. Then, as a second step, a technological solution is proposed, and as a third step, the system was evaluated through performance and user testing. As part of the technological solution and to allow patient participation during the rehabilitation process, we have proposed a hybrid admittance control whose input is load cell or electromyography signals. The hybrid admittance control is intended for active therapy exercises, is easily implemented, and does not need musculoskeletal modeling to work. Furthermore, electromyography signals classification models and features were evaluated to identify the best settings for the cognitive human-robot interaction.

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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.

This paper proposes a robust algorithm based on a fixed-time sliding mode controller (FTSMC) for a Quadrotor aircraft. This approach is based on Lyapunov theory, which guarantees system stability. Nonlinear error dynamics techniques are used to achieve accurate trajectory tracking in the presence of disturbances. The performance of the FTSMC is compared with the typical non-singular terminal sliding mode controller (NTSMC) to evaluate its effectiveness. The numerical results show that FTSMC is more efficient than the typical NTSMC in disturbance reduction.

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.

An essential aspect to achieving safety with a UAV is that it operates within the limits of its capabilities, the available flight time being a key aspect when planning and executing a mission. The flight time will depend on the relationship between the available energy and the energy required by the UAV to complete the mission. This paper addresses the problem of estimating the energy required to perform a mission, for which a fuzzy Takagi–Sugeno system was implemented, whose premises were developed using fuzzy C-means to estimate the power required in the different stages of the mission. The parameters used in the fuzzy C-means algorithm were optimized using particle swarm optimization. On the other hand, an equivalent circuit model of a battery was used, for which fuzzy modeling was employed to determine the relationship between the open-circuit voltage and the state of charge of the battery, which in conjunction with an extended Kalman filter allows determining the battery charge. In addition, we developed a methodology to determine the minimum allowable battery charge level. From this, it is possible to determine the available flight time at the end of a mission defined as the flight time margin. In order to evaluate the developed methodology, a physical experiment was performed using an hexarotor UAV obtaining a maximum prediction error equivalent to the energy required to operate for 7 s, which corresponds to 2% of the total mission time.

This paper deals with the references generation for a team of unmanned aerial vehicles tethered to a ground station for inspection applications. In order to deploy the team of vehicles in a suitable location to cover the largest area, each vehicle is commanded to securely navigate in an area of interest while it is tethered to another vehicle or to a ground station. To generate the corresponding reference for each vehicle, we used a model predictive controller, which optimizes the desired trajectory based on the mission-defined constraints. To validate the effectiveness of the proposed strategy, we conducted a simulation and experimental tests with a team of consumer unmanned aerial vehicles tethered to a ground station.

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.

Building inspection is a vital task because infrastructure damage puts people at risk or causes economic losses. Thanks to the technological breakthroughs in regard to Unmanned Aerial Vehicles (UAVs) and intelligent systems, there is a real possibility to implement an inspection by means of these technologies. UAVs allow reaching difficult places and, depending on the hardware carried onboard, take data or compute algorithms to understand the environment. This paper proposes a real-time robust altitude control strategy for a quadrotor aircraft, also a convolutional neuronal network for crack recognition is developed. The main idea of this proposal is to lay the background for an autonomous system for the inspection of structures using a UAV. For the robust control, a combination of two control actions, one linear (PD) and another nonlinear (Sliding Mode) is used. The combination of these control actions allows increasing the system’s performance. To verify the satisfactory performance of proposed control law, simulations and experimental results with a quadrotor, in the presence of disturbances, are presented. For crack recognition in images, several experiments were carried out validating the proposed model. For CNN training, a database of cracks was built from images taken from the Internet.

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...

This article presents the mechanical design and simulation of a two-degree-of-freedom exoskeleton robot to assist the Sit-to-Stand (StoS) transfer of a person with reduced mobility due to spinal cord injury (SCI).Also featured is the simulation of a Robust, Non-singular, Fast Terminal Sliding Mode Control (RNFTSMC) to control the StoS transfer.The exoskeleton will be mounted on a base with four wheels and two brushless DC motors, it has a rechargeable battery allowing the translation of the prototype for up to 8 hr of continuous use, moreover this base has a center with the ability to compensate for changes in the inclination of the surface, thus reducing the sensation of falling when making use of service ramps in the translation of the user.

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.

A hybrid unmanned autonomous vehicle (UAV) combines the high-speed cruise capability of a fixed-wing airplane, with the hovering flight, vertical take-off and landing capabilities of a helicopter. The change between both flight modes refers to as a transition flight process. This paper presents the flight dynamics during the transition stage of a hybrid UAV of Dual Tilt-Wing type. A non-linear mathematical model is developed that includes the UAV complete dynamics, which presents significant changes in aerodynamic characteristics, especially during the transition flight. These changes are analyzed and characterized by flight tests and CFD simulations. The adaptation to the variation of aerodynamic characteristics caused by tilt angle changes of transition system is verified, so a PD controller for altitude is implemented.

This article addresses the development and experimental validation of a trajectory-tracking control for a miniature autonomous Quadrotor helicopter system (X4-prototype) using a robust algorithm control based on second-order sliding mode technique or also known as super-twisting algorithm in outdoor environments. This nonlinear control strategy guarantees the convergence in finite time to a desired path r(t) in the presence of external disturbances or uncertainties in the model affecting the appropriate behavior of our Quadrotor helicopter. For this purpose, a polynomial smooth curve trajectory is selected as a reference signal where the corresponding derivatives of the function are bounded. Moreover, we consider disturbances due to wind gusts acting on the aerial vehicle, and the reference signal is pre-programmed in an advanced autopilot system. The proposed solution consists of implementing a real-time control law based on super-twisting control using GPS measurements in order to obtain the position in the xy-plane to accomplish the desired trajectory. Simulation and experimental results of trajectory-tracking control are presented to demonstrate the performance and robustness of the proposed nonlinear controller in windy conditions.

Inertial stabilised platforms are increasingly popular with a large range of products available mainstream. Most items are controlled using popular algorithms that sometimes do not offer best achie...

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.

This short communication article presents an experiment to test the existence of mental workload (MWL) and adaptability of a human operator (HO) in handling force augmenting devices (FADs). An experiment is conducted where the HOs of three different ages are allowed to handle a FAD with high augmentation factor. Augmentation factor gives the factor by which the HO’s force is amplified. It is observed that the HOs were unable to stabilize the FAD for the first time. With the help of these experiments, it is observed that a human adapts itself to achieve a stable HA-FAD interaction. In another perspective, it can be observed that HO undergoes MWL to handle a FAD with high augmentation factor.

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.

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.

This paper presents the development of an exoskeleton mounted on a mobile base to assist people in the Sit-to-Stand action and focused in the rehabilitation of the hip and knees joints. The prototype consists of linear actuators distributed in such a way that they assist the movements of extension and flexion, in the sagital plane, in the hip and knee joints; also, the mobile base allows the transport of a person of up to 90kg. The interaction between the user and the exoskeleton is carried out by processing EMG signals from the user via a Myo Armband and using a classifier to recognise five hand gestures that, in combination of them, generate the instructions to the exoskeleton. A PID control law was programmed in a microcontroller use as slave attached to an embedded computer for tracking the trajectories obtained from the Capture Motion System. The dynamical model of the system is presented in the paper as well as simulation and experimental results.

This paper presents a Proportional-Derivative Control strategy for the non-linear PVTOL system without algebraic restrictions. The total thrust is computed using a non-linear feedback compensation so that the altitude reaches the desired reference. The horizontal position $x$ is then controlled by choosing the orientation angle $\theta$ as a smooth saturation function of $x$ and $\dot{x}$ . A proof of convergence is presented using a Lyapunov approach. The proposed control strategy is successfully tested in numerical simulations.

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 paper presents the development of an hybrid Unmanned Aerial Vehicle that combines the capabilities of Vertical Takeoff and Landing (VTOL) as well as the hover flight of an helicopter, with the autonomy, load capacity and speed offered by an airplane. We start from an aircraft concept that uses the Tilt-Rotor configuration to perform the transition phase from one flight mode to another and simultaneously we used Ducted-Fans for increasing the flight performance during the vertical flight phase. The aerodynamic design is developed using computational tools, such as XFLR5 for preliminary design and ANSYS FLuent®for the verification of the preliminary fixed wing design. While for the vertical flight, experimental tests were conducted in order to determine the lift system requirements by using Ducted-Fans. Afterwards, the manufacturing process derived from the aerodynamic design is presented. The avionics developed is described for handling the control surfaces during the airplane mode and the main lift system during the vertical flight as well as the integration of mechanism and sensors used. Finally, the obtained results from the conducted vertical flight tests at outdoors environments are presented in order to show the effectiveness of the aircraft concept.

In this chapter, various results concerning the stability of dissipative systems are presented. First, the input/output properties of several feedback interconnections of passive, negative imaginary, maximal monotone systems are reviewed. Large-scale systems are briefly treated. Then the conditions under which storage functions are Lyapunov functions are given in detail. Results on stabilization, equivalence to a passive system, input-to-state stability, and passivity of linear delay systems are then provided. The chapter ends with an introduction to \(H_{\infty }\) theory for nonlinear systems that is related to a specific dissipativity property, and with a section on Popov’s hyperstability.

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.

The use of autonomous vehicles in daily life is more commonly every day, we can find it in security missions, agriculture, windmills inspection and one of its main uses the processes of photogrammetry, because the new systems and technologies to perform the last one could give errors of centimeters in a topographic map. The studies of large areas are carried out with fixed-wing UAV, so it is necessary to ensure that the vehicle could follow a desired path even in presence of external disturbances, in order to avoid uncovered or wrong defined areas during the post-processing. In this article we analyzed and compared by simulation the use of a non-linear control technique with a PID control to stabilize the airplane’s attitude and height, to prove that in some cases only a linear control technique is enough to stabilize the UAV and also probe that the amount of energy to control the UAV is similar in both techniques. So the majority of computational resources can be assigned to object detection and collision avoidance tasks, for vehicles under 5 kilograms.