Search

This article presents the design of a control algorithm based on Artificial Neural Networks (ANNs) applied to a lower-limb exoskeleton, which is aimed to carry out walking trajectories during lower-limb rehabilitation. The interaction between the patient and the exoskeleton leads to model uncertainties and external disturbances that are always present. For this reason, the proposed control considers that the non-linear part of the model is unknown and is perturbed by external disturbances, which are estimated by an active disturbance rejection control via Artificial Neural Networks. To validate the proposed approach, a numerical simulation and an experimental implementation of the ANN-Controller are developed.

Modelling and controlling an electrical Power Generation System (PGS), which consists of an Internal Combustion Engine (ICE) linked to an electric generator, poses a significant challenge due to various factors. These include the non-linear characteristics of the system’s components, thermal effects, mechanical vibrations, electrical noise, and the dynamic and transient impacts of electrical loads. In this study, we introduce a fuzzy modelling identification approach utilizing the Takagi–Sugeno (T–S) structure, wherein model and control parameters are optimized. This methodology circumvents the need for deriving a mathematical model through energy balance considerations involving thermodynamics and the non-linear representation of the electric generator. Initially, a non-linear mathematical model for the electrical power system is obtained through the fuzzy c-means algorithm, which handles both premises and consequents in state space, utilizing input–output experimental data. Subsequently, the Particle Swarm Algorithm (PSO) is employed for optimizing the fuzzy parameter m of the c-means algorithm during the modelling phase. Additionally, in the design of the Parallel Distributed Compensation Controller (PDC), the optimization of parameters pertaining to the poles of the closed-loop response is conducted also by using the PSO method. Ultimately, numerical simulations are conducted, adjusting the power consumption of an inductive load.

In recent decades, the field of statistical linguistics has made significant strides, which have been fueled by the availability of data. Leveraging Twitter data, this paper explores the English and Spanish languages, investigating their rank diversity across different scales: temporal intervals (ranging from 3 to 96 h), spatial radii (spanning 3 km to over 3000 km), and grammatical word ngrams (ranging from 1-grams to 5-grams). The analysis focuses on word ngrams, examining a time period of 1 year (2014) and eight different countries. Our findings highlight the relevance of all three scales with the most substantial changes observed at the grammatical level. Specifically, at the monogram level, rank diversity curves exhibit remarkable similarity across languages, countries, and temporal or spatial scales. However, as the grammatical scale expands, variations in rank diversity become more pronounced and influenced by temporal, spatial, linguistic, and national factors. Additionally, we investigate the statistical characteristics of Twitter-specific tokens, including emojis, hashtags, and user mentions, revealing a sigmoid pattern in their rank diversity function. These insights contribute to quantifying universal language statistics while also identifying potential sources of variation.

In this paper, serial elastic actuators (SEAs) in conjunction with an accelerometer are proposed as force sensors to detect the intention of movement, and the SEA is proposed as a gentle actuator of a patient’s upper-limb exoskeleton. A smooth trajectory is proposed to provide comfortable performance. There is an offset trajectory between the link and the motor, which increases safety by preventing sudden movements, and the offset is equivalent to the torsional elastic spring constant. The proposed control law is based on a backstepping approach tested in real-time experiments with robust results in a 2-DoF upper-limb rehabilitation exoskeleton. The experimental results showed a sensitivity of 100% and a positive predictive value of 97.5% for movement intention detection.

This article presents a virtual swashplate mechanism for a mini helicopter in classic configuration. The propeller bases are part of a passive mechanism driven by main rotor torque modulaton, this mechanism generates a synchronous and opposite change in the propellers angle of attack, then the thrust vector tilts. This approach proposes to control the 6 degrees of freedom of the aircraft using two rotors. The main rotor controls vertical displacement and uses torque modulation and swing-hinged propellers to generate pitch and roll moments and the horizontal displacement while the yaw moment is controlled by the tail rotor. The dynamic model is obtained using the Newton-Euler approach and robust control algorithms are proposed. Experimental results are presented to show the performance of the proposed virtual swashplate in real-time outdoor hover flights.

The lack of general algorithms for the control of nonlinear systems is a generalized problem, especially when attempting to stabilize systems such as ground vehicles, which have uncertainties and are usually linearized under the assumption of small angles. To solve this problem, in this work, the implementation of a suboptimal discrete control is developed to stabilize an autonomous automobile. We assume the system is affine for the optimization procedure of finite horizon that allows us to find a solution while avoiding solving the Ricatti-type equation, commonly encountered in this kind of algorithm. This procedure is applied to the dynamical model of the lateral displacement and orientation errors of the vehicle that was discretized through the method of Euler. These nonlinear models discretized to compute a bounded control. The control is tested in different simulated scenarios to show the efficiency of the system for solving typical tasks for the path planning of an autonomous vehicle.

This paper proposes a new sensor using optical flow to stabilize a quadrotor when a GPS signal is not available. Normally, optical flow varies with the attitude of the aerial vehicle. This produces positive feedback on the attitude control that destabilizes the orientation of the vehicle. To avoid this, we propose a novel sensor using an optical flow camera with a 6DoF IMU (Inertial Measurement Unit) mounted on a two-axis anti-shake stabilizer mobile aerial gimbal. We also propose a robust algorithm based on Sliding Mode Control for stabilizing the optical flow sensor downwards independently of the aerial vehicle attitude. This method improves the estimation of the position and velocity of the quadrotor. We present experimental results to show the performance of the proposed sensor and algorithms.

Detecting people in images and videos captured from an aerial platform in wooded areas for search and rescue operations is a current problem. Detection is difficult due to the relatively small dimensions of the person captured by the sensor in relation to the environment. The environment can generate occlusion, complicating the timely detection of people. There are currently numerous RGB image datasets available that are used for person detection tasks in urban and wooded areas and consider the general characteristics of a person, like size, shape, and height, without considering the occlusion of the object of interest. The present research work focuses on developing a thermal image dataset, which considers the occlusion situation to develop CNN convolutional deep learning models to perform detection tasks in real-time from an aerial perspective using altitude control in a quadcopter prototype. Extended models are proposed considering the occlusion of the person, in conjunction with a thermal sensor, which allows for highlighting the desired characteristics of the occluded person.

This paper presents the development of a robust control algorithm to be applied in a knee and ankle joint exoskeleton designed for rehabilitation of flexion/extension movements. The goal of the control law is to follow the trajectory of a straight leg extension routine in a sitting position. This routine is commonly used to rehabilitate an injury on an Anterior Cruciate Ligament (ACL) and it is applied to the knee and ankle joints. Moreover, the paper presents the development and implementation of the robotic structure of the ankle joint to integrate it into an exoskeleton for gait rehabilitation. The development of the dynamic model and the implementation of the control algorithm in simulation and experimental tests are presented, showing that the proposed control guarantees the convergence of the tracking error.

This research work describes the development of a fully actuated 6 Degree of Freedom (DOF) Unmanned Underwater Vehicle (UUV), which can be used for environmental monitoring, three-dimensional (3D) reconstruction applications, as well a research platform. The main vehicle’s characteristics are: it is designed to have easy access to all components, it has eight thrusters in a vectored configuration, it is based on an open source ArduSub firmware, it has a vision system composed of a stereo camera and a powerful computer for image processing. The mechatronics design is presented, where the mechanical, electrical and electronics, and the vision system are described. Furthermore, a general dynamic model for 6 DOF based on Fossen’s methodology is presented. In addition, a reduced 3 DOF mathematical model is derived for control purposes, where the roll, pitch and depth dynamics are considered. To show the performance in trajectory tracking tasks, two classical control strategies are introduced: a Super Twisting Controller and a Robust Proportional Derivative (PD) Controller. Finally, in order to exhibit the satisfactory performance of the developed vehicle, some experiments were conducted with the Super Twisting and Robust PD Controllers, as well as a 3D reconstruction of a plastic cover on the pool wall.

This paper presents the development of an instrumented exoskeleton with baropodometry, electromyography, and torque sensors. The six degrees of freedom (Dof) exoskeleton has a human intention detection system based on a classifier of electromyographic signals coming from four sensors placed in the muscles of the lower extremity together with baropodometric signals from four resistive load sensors placed at the front and rear parts of both feet. In addition, the exoskeleton is instrumented with four flexible actuators coupled with torque sensors. The main objective of the paper was the development of a lower limb therapy exoskeleton, articulated at hip and knees to allow the performance of three types of motion depending on the detected user’s intention: sitting to standing, standing to sitting, and standing to walking. In addition, the paper presents the development of a dynamical model and the implementation of a feedback control in the exoskeleton.

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.

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.

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.

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.

This paper addresses the tracking control of quadrotors flying outdoors. Two control laws are combined and tested in real-time experiments. The aircraft attitude and the translational displacement are controlled using the backstepping approach, while the altitude is controlled using the sliding mode control strategy. In both cases, new modifications are introduced with respect to the existing classical algorithms. Concerning the backstepping algorithm, we introduce the dynamical model of the quadrotor in the controller design and this guarantees that the virtual input is bounded. On the other hand, the proposed sliding mode control assures that the vehicle's altitude converges in finite time to the desired reference, even when uncertainties are considered in the system. The proposed controller is tested in an outdoor environment and the experiments highlighted the controllers' reliability. Additionally, the performance of the closed-loop plant with the proposed controllers is compared with the performance given by a proportional-derivative controller.

The increasing development in aerial vehicles shows a wide range of configurations for different requirements. Many of them combine conventional configurations’ features to take advantage of their qualities, such as performing a cruise flight as an airplane and hovering like a helicopter. Thereby, this study analyzes the modeling and control of a pair of fixed-wing airplanes joined together to form a larger rotor that incorporates valuable features in missions with aerial vehicles. The model uses the Lagrange approach to obtain the motion equations in the flight plane, and two control strategies are proposed to regulate the movement in the horizontal plane: a cyclic proportional derivative control and a positive function. Both controls generate a sinusoidal signal to regulate the thrust of the motors, and this leads to the generation of pulses that direct and move the vehicle toward a desired position until it is reached. Our analysis is validated by simulation that shows how both controls govern the center of mass position of the rotating planes, and it also shows the airplanes’ trajectory. The results show good performance.

This work proposes a simplified control method to stabilize the model of a nonlinear Planar Vertical Take-Off and Landing (PVTOL) system when a constant force is applied in the horizontal axis. Since the stability analysis is based on a Lyapunov function, exponential stability is guaranteed when the initial conditions fall inside a domain of attraction that is also specified. The performance of the suggested control algorithm is demonstrated using numerical simulations.

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.

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.

We present an automatic agave detection method for counting plants based on aerial data from a UAV (Unmanned Aerial Vehicle). Our objective is to autonomously count the number of agave plants in an area to aid management of the yield. An orthomosaic is obtained from agave plantations, which is then used to create a database. This database is in turn used to train a Convolutional Neural Network (CNN). The proposed method is based on computer image processing, and the CNN increases the detection performance of the approach. The main contribution of the present paper is to propose a method for agave plant detection with a high level of precision. In order to test the proposed method in a real agave plantation, we develop a UAV platform, which is equipped with several sensors to reach accurate counting. Therefore, our prototype can safely track a desired path to detect and count agave plants. For comparison purposes, we perform the same application using a simpler algorithm. The result shows that our proposed algorithm has better performance reaching an F1 score of 0.96 as opposed to 0.57 for the Haar algorithm. The obtained experimental results suggest that the proposed algorithm is robust and has considerable potential to help farmers manage agave agroecosystems.

Hybrid Unmanned Aerial Vehicles (H-UAVs) are currently a very interesting field of research in the modern scientific community due to their ability to perform Vertical Take-Off and Landing (VTOL) and Conventional Take-Off and Landing (CTOL). This paper focuses on the Dual Tilt-wing UAV, a vehicle capable of performing both flight modes (VTOL and CTOL). The UAV complete dynamic model is obtained using the Newton–Euler formulation, which includes aerodynamic effects, as the drag and lift forces of the wings, which are a function of airstream generated by the rotors, the cruise speed, tilt-wing angle and angle of attack. The airstream velocity generated by the rotors is studied in a test bench. The projected area on the UAV wing that is affected by the airstream generated by the rotors is specified and 3D aerodynamic analysis is performed for this region. In addition, aerodynamic coefficients of the UAV in VTOL mode are calculated by using Computational Fluid Dynamics method (CFD) and are embedded into the nonlinear dynamic model. To validate the complete dynamic model, PD controllers are adopted for altitude and attitude control of the vehicle in VTOL mode, the controllers are simulated and implemented in the vehicle for indoor and outdoor flight experiments.

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.

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.

This article addresses the problem of altitude tracking for unmanned aircraft system when the altitude velocity is unknown, because in a practical implementation, the available sensors used to measure the vehicle’s altitude (barometer, global positioning system, laser, etc.) do not provide the altitude velocity. We propose a control strategy based on both the super-twisting sliding mode controller as well as a high-order sliding mode observer to control and to estimate the altitude velocity, respectively. A comprehensive stability analysis for the combined controller–observer based on the Lyapunov stability theory is presented, ensuring the asymptotic convergence of the tracking error under external bounded disturbances. To demonstrate the performance and the effectiveness of the proposed solution, an extensive set of real-time experimental tests performed at outdoor environments is presented.

Resumen: Los exoesqueletos mecánicos son robots acoplados a las extremidades del cuerpo humano enfocados en el incremento de su fuerza, velocidad y rendimiento principalmente. Las principales aplicaciones son en la milicia, en la industria y en la medicina. El exoesqueleto se puede utilizar para la rehabilitación de las extremidades cuando por causas de algún accidente o enfermedad se tiene una actividad muscular reducida o nula. En este artículo se presenta un exoesqueleto de dos grados de libertad para realizar ejercicios de rehabilitación para tobillo y rodilla. El diseño y fabricación del exoesqueleto está basado en la instrumentación de una ortesis del miembro inferior derecho. El Exoesqueleto utiliza sensores que estiman la fuerza producida por el humano y se encuentran incorporados en los actuadores de tipo SEA (Series Elastic Actuator) que se utilizan para amplificar la fuerza humana. Además mediante sensores se estima la posición y velocidad angular de las articulaciones, que se utilizan para controlar el movimiento de la pierna. En el artículo se presentan: un estudio del modelo dinámico del exoesqueleto y de los actuadores acoplados por medio del método de perturbaciones singulares, el diseño de un control basado en la suma de fuerzas generadas por el humano y el exoesqueleto, el diseño y fabricación del prototipo experimental y sus actuadores. Se realizaron simulaciones que muestran el buen desempeño del controlador propuesto. Los resultados experimentales muestran que existe una amplificación de la fuerza generada por el portador y amplificada por la mecánica del exoesqueleto, ofreciendo una disminución en el esfuerzo del usuario para mantenerse de pie y realizar ejercicios de flexión y extensión de las articulaciones. De manera que la amplificación de la fuerza puede aumentarse o disminuirse según se necesite, permitiendo al usuario una mejora evolutiva hasta llegar a la rehabilitación completa. Abstract: Exoskeletons are robots attached to the extremities of the human body focused on increasing their strength, speed and performance primarily. The applications are in the military, industry and medical. The exoskeleton can be used for the rehabilitation of limbs because of accident or illness that can cause little muscle activity or null. This article presents an exoskeleton of two degrees of freedom that is used to ankle and knee exercise rehabilitation. The design and manufacture of the exoskeleton is based on the instrumentation of a right lower limb orthoses. The exoskeleton contains sensors to estimate the force produced by a human and contains SEA actuators (Serial Elastics Actuators) that used to amplify the human force. Also contains sensors to estimate the position and angular velocity in joints. This paper presents in general: a study of the dynamic model of the exoskeleton and actuators coupled through the singular perturbation method, the design of a control based on the sum of forces generated by the human and the exoskeleton, and the design and manufacture of an experimental prototype. The simulation result shows that the sum of forces between the human and the exoskeleton is controlled to obtain a desired angular position of the joints (knee and ankle). Experimental results show that exist a human force amplification generated by the exoskeleton, providing a reduction in the patient's effort to remain standing and bending exercises. Then force amplification can be increased or decreased as needed in different workouts that will allow the user an evolutionary improvement to achieve a full rehabilitation. Palabras clave: Exoesqueleto Mecánico, Rehabilitación, Control de Fuerza, Actuador SEA., Keywords: Mechanical Exoskeleton, Rehabilitation, Force control, SEA Actuators.

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’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 recent years, solar energy has been used as an energy source for many different applications. Currently in the area of Unmanned Aerial Vehicles (UAVs), there are research studies that incorporate this renewable energy technology to increase the vehicle’s autonomy. This technique also needs particular construction techniques and electronic boards, designed to reduce weight and increase the efficiency of all solar systems on board the UAV. As is well known, the amount of generated solar energy could be increased throughout a day a sun tracking technique is added. The present paper proves that the roll angle of a fixed wing UAV can be used to track the sun to increase the energy generated by the solar panels placed on the wing. In that case, the plane’s attitude must be compensated with the yaw angle control to be able to perform a photogrammetric mission. This will be achieved using a control strategy based on the super-twisting technique that ensures convergence in finite time even in the presence of bounded perturbations. The design of the control laws as well as the numerical simulation and real flight results are shown to validate the use of the sun tracking system.

Resumen: En este artículo se presenta la estabilización de vuelo de un helicóptero con cuatro rotores utilizando transductores inerciales y la información visual de una cámara. Utilizando el flujo óptico experimentado por el sensor visual se realiza la estimación de la velocidad traslacional en el plano x-y, de la posición y del ángulo de guiñada del helicóptero. En tanto los ángulos de orientación de alabeo y cabeceo junto con las velocidades angulares en todos los ejes (Ï,θ y Ï) son estimados utilizando filtros complementarios, los cuales son aplicados a las señales obtenidas de la central inercial. El flujo óptico es obtenido utilizando el método de Lucas-Kanade Piramidal, el cual permite detectar movimientos relativamente rápidos y es de fácil implementación computacional. Además, la información provista por los girómetros es también utilizada para eliminar la componente de flujo óptico generada por los movimientos de rotación experimentados en los ejes de alabeo y cabeceo que afectan directamente la estimación de la velocidad traslacional. Los resultados experimentales son presentados y muestran un desempeño satisfactorio del helicòptero en tiempo real. Palabras clave: Control de aeronaves, visión por computadora, navegación de robots

This paper deals with an experimental comparison between the proportional integral derivative (PID) control law and the adaptive nonlinear state feedback control, both applied on the AC-ROV underwater vehicle. The experimental results evaluate the closed-loop behaviour of the system under each controller in various operating conditions in order to compare how robust they are towards parameters' change and how they can reject external disturbances. It was concluded that the adaptive controller ensures a faster convergence and can adapt to a change of parameters as well as compensate for external disturbances. The PID needs to be retuned for every parameter change and is more sensitive to external disturbances.

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.

A real-time localization algorithm is presented in this paper. The algorithm presented here uses an extended Kalman filter and is based on Time Difference Of Arrivals (TDOA) measurements of radio signal. The position and velocity of an Unmanned Aerial Vehicle (UAV) are successfully estimated in closed-loop in real-time, both in hover and path following flights. Relatively small position errors obtained from the experiments prove the good performance of the proposed algorithm.