Movable Platform Research Articles

Droplet Microfluidic-Based Low-Cost and High-Speed Microsphere Array Direct Writing Technology and Its Applications.

Microsphere arrays have significant applications and broad development prospects in various fields and disciplines. The simple, efficient, low-cost, automatic, and controllable preparation of microsphere arrays in multiple dimensions and morphologies is still a significant challenge. Here, a novel microsphere array direct writing technology was developed using a low-cost portable droplet microfluidic device and a high-precision XY movable platform. The proposed technology provided a powerful platform for the direct-writing preparation of microsphere arrays and was successfully applied to the precise and controllable fabrication of microsphere arrays with different sizes, shapes, structures, and arrangements. Additionally, gel microsphere arrays with metal ion patterns were fabricated using the microsphere arrays as templates and exhibited excellent performance in the visual analytical detection of heavy metal ions. Moreover, the simulated microsphere arrays offer a promising platform for rapidly generating high-viability and uniform 3D tumor spheroids. Therefore, given the superiority of this technology and the great potential of microsphere arrays, this simple high-speed microsphere array direct writing technology has a promising application in the multidisciplinary intersection of chemical, biological, and material sciences.

Fixed-Time Controller for Altitude/Yaw Control of Mini-Drones: Real-Time Implementation with Uncertainties

Gradually, it has become easier to use aerial transportation systems in practical applications. However, due to the fixed-length wire, recent studies on load-suspended transportation systems have revealed some practical constraints, especially when using quadrotor unmanned aerial vehicles (UAVs). By actively adjusting the distance between the quadrotor and the payload, it becomes possible to carry out a variety of challenging tasks, including traversing confined spaces, collecting samples from offshore locations, and even landing a payload on a movable platform. Thus, mass variable aerial transportation systems should be equipped with trajectory tracking control mechanisms to accomplish these tasks. Due to the above-mentioned reasons, the present paper addresses the problem of the altitude/yaw tracking control of a mini-quadrotor subject to mass uncertainties. The main objective of this paper is to design a fixed-time stable controller for the perturbed altitude/yaw motions, based on recent results using the fixed-time stability approach. For comparison reasons, other quadrotor motion controllers such as dual proportional integral derivative (PID) loops were considered. To show its effectiveness, the proposed fixed-time controller was validated on a real mini-quadrotor under different scenarios and has shown good performance in terms of stability and trajectory tracking.

Mobile robotics platform for strawberry sensing and harvesting within precision indoor farming systems

AbstractIndoor farming is expected to have an increasing impact on future food and agricultural systems. It can produce crops year‐round without relying on weather patterns, bringing crop production systems closer to advanced manufacturing systems for industrial and consumer goods. Indoor farming also provides an ideal platform for implementing intelligence‐driven and empowered agricultural systems that can autonomously gather/process data, build a knowledge base, provide management decision support, and execute crop cultural tasks. Towards that goal, a mobile robotics platform (MRP) has been under development. This platform will provide new capabilities for implementing indoor farming cyber–physical systems. The ultimate purpose is to equip the MRP with systematically integrated capabilities of perception, reasoning, learning, communication, and task planning/execution for use in precision indoor farming systems. This presentation reports the current state of MRP's development. The MRP can monitor the growing status of individual strawberry plants and fruit with a perception system and nondestructively harvest individual ripe strawberries with an onboard robot. The robotic system has a stereo camera, a six‐degrees of freedom robotic manipulator, and a pneumatically actuated soft gripper (i.e., end‐effector) mounted on an autonomous mobile base. These subsystems were specifically chosen from commercially available products. An open‐loop fruit positioning and handling algorithm, in a software form, capable of performing the tasks of fruit detection, localization, grasping, detachment, and placement, has been developed. The location and ripeness of each fruit can be simultaneously obtained through deep learning techniques. We found that a mean average precision value of 96.4% for ripe strawberries could be obtained in a custom indoor strawberry data set. Three‐dimensional (3D) locations of individual strawberries are used in the motion planner to guide the movements of the mobile platform, manipulator, and end‐effector. The robot can autonomously classify each strawberry fruit's growth scene through the fusion of the detection results and the corresponding depth information, to determine whether to perform the harvesting action. The accuracy of the proposed strawberry growth scene categorization approach is 89.1%, and the weighted‐averaged F1 score is 0.7. The soft gripper can approach and gently hold a target strawberry fruit. A novel approach for fruit detachment has been developed to separate the fruit's sepal and the stalk by a drag‐and‐rotate motion. The experiments conducted in a commercial indoor strawberry farm showed an overall success rate of 78% in handling harvestable strawberries with a damage rate of 23%. The average harvesting cycle time was found to be 10.5 s. We found that poor fruit visibility mainly reduced the success rate of the target fruit's robotic detection and grasping action. The grasping and detachment tasks were affected by fruit size and stalk length. These factors together determined the overall harvesting performance of the robotic system. The robotic system showed better performance when harvesting fruit of small size (width is less than 31 mm and height is less than 33 mm) with a medium stalk (between 81 and 101 mm). The MRP's functions are expected to be transferable and expandable to other crop production monitoring and cultural tasks.

ОПРЕДЕЛЕНИЕ ИНДЕКСА УПРАВЛЯЕМОСТИ И ВЫЯВЛЕНИЕ ОСОБЫХ ПОЛОЖЕНИЙ ПАРАЛЛЕЛЬНОГО МАНИПУЛЯТОРА

The article presents a model, tools, methodology and results of identifying special provisions when planning the movement of a parallel manipulator such as the Gough-Stewart platform. Special positions are understood as positions having geometric uncertainty, singularity. Singular positions are estimated by analyzing the Jacobian matrix using its singular value decomposition. The calculation of the Jacobi matrix and its singular values is performed using special libraries of the high-level Python programming language. The presence of special positions in the workspace is analyzed using the dexterity index, which characterizes the ratios of the singular values of the singular value decomposition of the Jacobian matrix. A series of computational experiments are carried out to calculate the dexterity index, identify and analyze special positions in the working area. The results of a computational experiment for various design versions of the platform, which differ in the ratio of the radii of the movable platform and the fixed base, are presented. The analysis of the characteristic features of the formation of singularity zones in their working zones is carried out and design options are identified that have the maximum dexterity index of the working area. The presented approach is applicable in the framework of the development, modernization, optimization of structural elements of parallel structure manipulators.

A 2R1T Redundantly Actuated Parallel Manipulator With an Offset Moving Platform and Fixed Linear Actuators

Abstract Redundantly actuated parallel manipulators with two rotations and one translation (2R1T RAPMs) have the potential for machining complex surfaces, where a large orientation workspace and high stiffness are required. Considering the advantages of an offset moving platform, such as an enlarged orientation workspace and improved stiffness, a novel 2R1T (2PRR)R-PRS-PSS RAPM with an offset moving platform is proposed in this paper, called M2. Compared with the existing 2R1T RAPM with an offset moving platform, the main advantage of the proposed RAPM is that the heavy motors of four limbs are mounted on the base to reduce the movable mass and improve dynamic response. The kinematical analysis is investigated, including mobility, inverse, forward kinematics, and singularity analysis. Meanwhile, comprehensive evaluations of the properties of the offset moving platform and actuation redundancy are carried out. Compared with M2 RAPM’s form without an offset in moving platform, i.e., no auxiliary platform, and M2 RAPM’s nonredundantly actuated form, the proposed M2 RAPM can achieve a larger orientation workspace and higher stiffness. Particularly, the maximum stiffness of the proposed M2 is 68.8% larger than its form without an auxiliary platform. Finally, the dimensional parameters of the proposed M2 are optimized to obtain an improved satisfactory workspace.

RESEARCH ON IMPACT LOADING OF A MOBILE TRACKED PLATFORM WITH AN AUTONOMOUS STABILIZATION SYSTEM

The work presents a developed 3D model of a mobile robotic platform with an autonomous stabilization system for reconnaissance operations. Mobile robotic platforms have been found to be widely used in intelligence because they can help gather information from dangerous and hard-to-reach places and reduce the risk to the lives of intelligence personnel. Unmanned aerial vehicles and mobile robotic platforms with tracks are mainly used in reconnaissance. An important distinguishing quality of tracked mobile robots is their maneuverability. Having an independent drive for each of the tracks separately, the mobile robot can easily change the direction of its own movement. A study on shock loads (external influences on the system that can cause deformation, damage or destruction) of a mobile tracked platform with an autonomous stabilization system was conducted and the obtained results were described. The SOLIDWORKS software environment was used to model the design of the mobile platform. For numerical studies on impact loads, it is advisable to use linear elastic isotropic materials and bilinear Mises plastic materials. The results of the simulation of the movement of the mobile platform of the developed structure and the stresses in the collision with different speeds of 1, 5, 10, 25 m/s and the platform material carbon steel and rubber are presented. It was established that when a mobile platform collides with speeds of up to 25 m/s, the maximum stresses do not exceed 1.85 MPa, which gives a sufficient margin of strength in the event of impact loads for the selected material of the mobile platform. The use of steel inserts allows you to reduce the value of the maximum contact stresses under impact load, but increases the cost of the mobile platform, increases the total weight and, accordingly, reduces the operating time from the installed power batteries.

Fluorescence-Enhanced Microfluidic Biosensor Platform Based on Magnetic Beads with Highly Stable ZnO Nanorods for Biomarker Detection

Existing affinity-based fluorescence biosensing systems for monitoring of biomarkers often utilize a fixed solid substrate immobilized with capture probes limiting their use in continuous or intermittent biomarker detection. Furthermore, there have been challenges of integrating fluorescence biosensors with a microfluidic chip and low-cost fluorescence detector. Herein, we demonstrated a highly efficient and movable fluorescence-enhanced affinity-based fluorescence biosensing platform that can overcome the current limitations by combining fluorescence enhancement and digital imaging. Fluorescence-enhanced movable magnetic beads (MBs) decorated with zinc oxide nanorods (MB-ZnO NRs) were used for digital fluorescence-imaging-based aptasensing of biomolecules with improved signal-to-noise ratio. High stability and homogeneous dispersion of photostable MB-ZnO NRs were obtained by grafting bilayered silanes onto the ZnO NRs. The ZnO NRs formed on MB significantly improved the fluorescence signal up to 2.35 times compared to the MB without ZnO NRs. Moreover, the integration of a microfluidic device for flow-based biosensing enabled continuous measurements of biomarkers in an electrolytic environment. The results showed that highly stable fluorescence-enhanced MB-ZnO NRs integrated with a microfluidic platform have significant potential for diagnostics, biological assays, and continuous or intermittent biomonitoring.

Modeling and performance analysis of elastostatic stiffness of kinematically redundant parallel mechanisms

An analytical elastostatic stiffness modeling approach for kinematically redundant parallel mechanisms (KR-PMs) according to screw theory and the second theorem of Castigliano is proposed. The 2-UPR/PRPU and 2-PUPR/PRPU KR-PMs are used as two examples of KR-PMs to validate the precision of the proposed approach. The relative error is less than 1.55% when the theoretical model is compared to the FEA model. The PM’s stiffness performance is assessed using the minimum linear displacement stiffness performance index, which is based on the theoretical model. By integrating Particle Swarm Optimization (PSO) with polynomial fitting technology, an analytical mapping model of the response surface between the optimal actuating distances and the moving platform (MP)’s given position and orientation is established. It is demonstrated that 2-UPR/PRPU and 2-PUPR/PRPU KR-PMs can significantly enhance the stiffness performance when compared to the stiffness performance of 2-UPR/RPU PM.

Machine Learning-Based Solutions for Handover Decisions in Non-Terrestrial Networks

The non-terrestrial network (NTN) is a network that uses radio frequency (RF) resources mounted on satellites and includes satellite-based communications networks, high altitude platform systems (HAPS), and air-to-ground networks. The fifth generation (5G) and NTN may be crucial in utilizing communication infrastructure to provide 5G services in the future, anytime and anywhere. Based on the outcome of the Rel-16 study, the 3rd generation partnership project (3GPP) decided to start a work item on an NTN in 5G new radio (NR) Rel-17, and the focus of the study was on mobility management procedures, due to the movements of NTN platforms; especially, low earth orbit (LEO) satellites. Handover enhancements were discussed to tackle the frequent handover due to the fast satellite movement. Therefore, the major problem of handover in LEO satellite systems was the signaling storm created by handing over all user equipment (UE) in a cell to a new cell because when the UE crosses the boundary between the neighboring cell of a satellite, an intra-satellite or cell handover occurs; thus, all users in a cell are expected to experience a change of cell due to handover every few seconds. In addition, UE location is not easy to define due to moving cell/beam situations. In this study, we propose machine learning-based solutions for handover decisions in non-terrestrial networks for cell handovers or intra-satellite handovers to reduce signaling storms during handovers where the handover requests will be executed by clustered users. First, the dataset was generated by the simulator that simulates communication between users and satellites. Second, we preprocessed the data, and also used the feature creation technique to create the distance feature using the Haversine formula, and then applied clustering and classification algorithms. The experimental results show that the distance between a user and its cell center is an important parameter for handover decisions in NTN, and the random forest outperforms all models with a higher accuracy of 99% along with a better F1-score of 0.9961.

Agricultural Autonomous Robotic Platform Motion Control

A model of the movement of a robotic platform adapted to the conditions of an industrial orchard is proposed. (Research purpose) Development of a motion control system for an autonomous robotic wheeled platform based on inertial and satellite navigation and traversed path calculation, which will allow it to move in an apple orchard and automatically perform various technological operations, such as fertilization, growth diseases control of, fruit harvesting. (Materials and methods) A mathematical model was developed to control the movement of a robotic platform, taking into account the turning radii of three types, the length of the arc of the performed circle, the speed of movement in the garden plantation rows using a garden electronic map. The method used allows implementing a program for the robotic platform automatic movement around a typical orchard using a minimum set of sensors, significantly reducing the load on the onboard computer processor and memory. Software, developed in the Python programming language, enables plotting the robotic platform route, displaying the movement trajectory, and indicating the positioning accuracy at each point in relation to the trees in the garden plantation rows, the movement speed and the wheel rotation angle. (Results and discussion) The robotic platform managed to autonomously pass the preset routes, while the interaction of the software and the robotic platform hardware was provided. A field testing of the developed software was performed. (Conclusions) The specified accuracy of the robotic platform positioning was confirmed for the 3.5-meter aisles of intensive orchards. The maximum deviation from the task map using satellite and inertial navigation system was 164 millimeters, which complies with the agrotechnical requirements for mechanized fruit harvesting.

Research on Star Sensor-based Space Debris Detection and Positioning Technology

As an important part of space situational awareness, space-based surveillance of space debris is of great significance for understanding and protecting space resources. With the increasing number of spacecraft operating in the Earth's orbit, both the environment and the space security situation have gradually deteriorated. The accurate detection of small, dim targets in space is the technical basis of space-based debris monitoring; however, several difficulties exist in this field. Since space targets reflect low light energy, the number of pixels occupied by the target is small, and they do not reveal shape or texture characteristics. Space debris is therefore easily confused with background stars, leading to many false alarm targets, and making source detection, recognition, and tracking challenging. Accurate source positions for small and dim space targets are therefore important motivators in our project. However, the positioning accuracy of existing space-based monitoring platforms is limited by the position of the observation platform and the observable time period, due to the high-speed movements of the satellite platform and the observation target. The observation efficiency of existing space-based monitoring platforms is also low, which has certain limitations in practical applications. The high-precision measurement of target positions is thus inhibited when using existing space-based monitoring platforms. The aim of this research is to use an autonomous recognition algorithm based on a compound calibration star grid pattern for star identification. This study utilized a national advanced research project from the National High Technology Research and Development Program and used a star sensor for space debris monitoring, allowing dim and small space debris to be distinguished from stars. This research proposes a target detection technology path based on local sky reference star image comparison to detect weak and small targets in the background of star images. This technology enables the rapid, effective recognition and high-precision positioning of small, dim space targets.

Research on the Line of Sight Stabilization Control Technology of Optronic Mast under High Oceanic Condition and Big Swaying Movement of Platform

To realize high-performance line of sight (LOS) stabilization control of the optronic mast under high oceanic conditions and big swaying movements of platforms, a composite control method based on an adaptive radial basis function neural network (RBFNN) and sliding mode control (SMC) is proposed. The adaptive RBFNN is used to approximate the nonlinear and parameter-varying ideal model of the optronic mast, so as to compensate for the uncertainties of the system and reduce the big-amplitude chattering phenomenon caused by excessive switching gain in SMC. The adaptive RBFNN is constructed and optimized online based on the state error information in the working process; therefore, no prior training data are required. At the same time, a saturation function is used to replace the sign function for the time-varying hydrodynamic disturbance torque and the friction disturbance torque, which further reduce the chattering phenomenon of the system. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The applicability of the proposed control method is validated by a series of simulations and experiments.

New Approach of the Variable Fractional-Order Model of a Robot Arm

This paper proposes a simple mathematical model based on the variable fractional-order difference equation of a robot arm. The model of the described arm does not consider the impact of the movement of the mobile platform, it was assumed that all degrees of freedom would be taken away from it. The implementation of the task was divided into two stages. First, a mechanical model was developed. In order to estimate the torques of nodal propulsion motors, a description of the components of the Lagrange equation for the considered system, i.e., energy, power, and external interactions, and derivation of the equations of motion of the tested manipulator based on the Lagrange equation was made. An additional criterion was also considered in the selection of drives in the kinematic nodes of the links, which was to set the manipulator in a vertical position at a specific time. Processing the measured data of a robot arm, model parameters were selected, and the order function was chosen. The second stage was a simulation, whose results were compared with the collected data.

Upward perturbations trigger a stumbling effect

BackgroundVertical perturbations are one major cause of falling. Incidentally, while conducting a comprehensive study comparing effects of vertical versus horizontal perturbations, we commonly observed a stumbling-like response induced by upward perturbations. The present study describes and characterizes this stumbling effect. MethodsFourteen individuals (10 male; 27 ± 4 yr) walked self-paced on a treadmill embedded in a moveable platform and synchronized to a virtual reality system. Participants experienced 36 perturbations (12 types). Here, we report only on upward perturbations. We determined stumbling based on visual inspection of recorded videos, and calculated stride time and anteroposterior, whole-body center of mass (COM) distance relative to the heel, i.e., COM-to-heel distance, extrapolated COM (xCOM) and margin of stability (MOS) before and after perturbation. ResultsFrom 68 upward perturbations across 14 participants, 75% provoked stumbling. During the first gait cycle post-perturbation, stride time decreased in the perturbed foot and the unperturbed foot (perturbed = 1.004 s vs. baseline = 1.119 s and unperturbed = 1.017 s vs. baseline = 1.125 s, p < 0.001). In the perturbed foot, the difference was larger in stumbling-provoking perturbations (stumbling: 0.15 s vs. non-stumbling: 0.020 s, p = 0.004). In addition, the COM-to-heel distance decreased during the first and second gait cycles after perturbation in both feet (first cycle: 0.58 m, second cycle: 0.665 m vs. baseline: 0.72 m, p-values<0.001). During the first gait cycle, COM-to-heel distance was larger in the perturbed foot compared to the unperturbed foot (perturbed foot: 0.61 m vs. unperturbed foot: 0.55 m, p < 0.001). MOS decreased during the first gait cycle, whereas the xCOM increased during the second through fourth gait cycles post-perturbation (maximal xCOM at baseline: 0.5 m, second cycle: 0.63 m, third cycle: 0.66 m, fourth cycle: 0.64 m, p < 0.001). ConclusionsOur results show that upward perturbations can induce a stumbling effect, which – with further testing – has the potential to be translated into balance training to reduce fall risk, and for method standardization in research and clinical practice.

Research on the Calibration Method of Laser Arch Measuring Instrument

In view of the inconvenience caused by the lack of relevant calibration methods for the laser arch measuring instrument, this paper obtains the main components of the error based on the analysis of the principle of the arch measuring instrument, proposes the calibration methods for each error, and carries out experimental verification. The results show that the error is mainly angle error and distance error. The influence of angle error on the results decreases with the increase of the angle. According to the influence of ranging error and angle error in practical use, the methods of measuring the ranging error of the arch measuring instrument with a standard steel tape and measuring its vertical error and angle error with a movable vertical lifting two-dimensional platform are designed. The experimental results show that the calibration method is feasible.

Improved Coprime Array Designs Based on Moving Platform for Direction of Arrival Estimation

In this article, we mainly propose two improved coprime arrays (CAs) on array motion, ImCAAM1 and ImCAAM2, for direction of arrival (DOA) estimation, which can generate a longer consecutive difference co-array. Both the designs can solve the problem that part of lags, not surrounded by holes in difference co-array, have invalid use, when considering moving sparse array. The first scheme primarily implements two operations: compressing the interelement spacing of one subarray and staggering a certain distance between two subarrays. Two operations make contributions to increasing consecutive degrees of freedom (cDOF). Whereas the second one is able to further fill the remaining holes located at both the ends of virtual array. With the interelement spacing compress factor, equal to the number of elements of another subarray, and re-staggering the distance between subarrays, we can eventually obtain a longer full-populated virtual array. Finally, numerical simulations are presented to verify the efficacy of the proposed sparse array geometries using the subspace-based DOA estimation algorithm in terms of cDOF, spatial spectrum, and DOA estimation accuracy.

Analysis of middle-to-far wake behind floating offshore wind turbines in the presence of multiple platform motions

Understanding the unsteady characteristics of the mid-to-far wake and comprehension of the aerodynamic performance of floating offshore wind turbines is essential for the further development of offshore wind farms. In this perspective, a developed Actuator line model is utilized to analyze an offshore turbine on four different platforms. The model reliability was examined through three sets of validations involving turbine output in fixed and floating conditions and wake expansion in terms of size and rate. The affected relative velocity by the platform motion contributes to the wake deformation and temporal effects on induced velocity. Angular platform motions produce a non-axisymmetric helical wake that raises the chance of meandering wake patterns. It was founded although platform movement generally can boost the recovery of mean velocity value, it may amplify the amplitude of velocity deficit fluctuation at further downstream by encouraging interactions and merging vortex rings. Consequently, the wake propagates into a form of stronger circles whose period, strength, and center are functions of turbine movement and operation conditions. By providing a computationally efficient tool, the findings emphasize the importance of wake propagation in designing and assessing farm layouts that operate in the presence of significant multi-motions of floating offshore wind turbines.

Adjustable Vibration Exciter Based on Unbalanced Motors.

In European industry, such as metallurgical, mining and processing, construction, food, and chemical, vibration exciters are used, which indicates their wide and, in some cases, unique technological capabilities. The most common are electromagnetic and unbalanced vibration exciters. The advantages of electromagnetic vibration exciters include the ability to control the amplitude of the vibration by changing the electrical power supplied; the disadvantages are high material consumption. However, unbalanced vibration exciters have low energy efficiency, which is associated with difficult start-up conditions and with an overestimated mechanical power of the vibration exciter in relation to the power required by the technology itself, which is due to the need to minimize the effect of the technological load on the operating mode of the vibrating unit. Adjusting the amplitude of the disturbing force of unbalanced vibration exciters, regardless of the vibration frequency, will make it possible to reduce the installed power of the unit by passing the resonant frequency with a minimum disturbing force and compensating for the effect of the process load by means of a closed-loop electric drive. In the course of the study, an analytical description of the interaction of the rotating unbalances located on a common movable platform was obtained. On the basis of these analytical dependencies, a mathematical model was developed that takes into account the dynamic characteristics of a frequency-controlled asynchronous electric drive of a closed-loop control system for the mutual arrangement of rotating unbalances. The simulation results confirmed the possibility of using the specified electric drive to control the oscillation amplitude directly in the process of operation of a four-unbalanced vibration exciter. A physical experiment was carried out to determine the transient processes of changing the angular velocity of an induction motor with an abrupt change in the frequency converter setting. On the basis of this experiment, the previously created mathematical model was refined in terms of describing the dynamic parameters of the electric drive. The proposed structure of the control system, the performance of which has been confirmed by mathematical modeling, makes it possible to implement an adjustable four-unbalanced vibration exciter using single commercially available asynchronous vibrators.

Development and Evaluation of Fuzzy Logic Controllers for Improving Performance of Wind Turbines on Semi-Submersible Platforms under Different Wind Scenarios

Among renewable energy technologies, wind energy features one of the best possibilities for large-scale integration into power systems. However, there are specific restrictions regarding the installation areas for this technology, thus resulting in a growing, yet restricted, rate of penetration of the technology because of the limited viable sites onshore or in shallow waters. In this context, the use of offshore semi-submersible platforms appears as a promising option, which additionally enables the incorporation of other elements, such as wave energy converters or aquaculture. Nevertheless, this kind of offshore facility involves interactions between platform movements and the wind turbine, increasing the complexity of the system, causing traditional control techniques to not be able to fully cope with the dynamics of the system, and thus limiting the efficiency of energy extraction. On the contrary, the use of intelligent control techniques is an interesting option to take full account of the said interactions and to improve energy capture efficiency through the control of the pitch of the blades, especially under turbulent, above-rated wind profiles. This work presents an original fuzzy logic controller that has been validated by comparing it with previously validated controllers, following a developed methodology that allows comparison of controllers for wind turbines in semi-submersible platforms using performance indexes.

Interaction with a Hand Rehabilitation Exoskeleton in EMG-Driven Bilateral Therapy: Influence of Visual Biofeedback on the Users' Performance.

The effectiveness of EMG biofeedback with neurorehabilitation robotic platforms has not been previously addressed. The present work evaluates the influence of an EMG-based visual biofeedback on the user performance when performing EMG-driven bilateral exercises with a robotic hand exoskeleton. Eighteen healthy subjects were asked to perform 1-min randomly generated sequences of hand gestures (rest, open and close) in four different conditions resulting from the combination of using or not (1) EMG-based visual biofeedback and (2) kinesthetic feedback from the exoskeleton movement. The user performance in each test was measured by computing similarity between the target gestures and the recognized user gestures using the L2 distance. Statistically significant differences in the subject performance were found in the type of provided feedback (p-value 0.0124). Pairwise comparisons showed that the L2 distance was statistically significantly lower when only EMG-based visual feedback was present (2.89 ± 0.71) than with the presence of the kinesthetic feedback alone (3.43 ± 0.75, p-value = 0.0412) or the combination of both (3.39 ± 0.70, p-value = 0.0497). Hence, EMG-based visual feedback enables subjects to increase their control over the movement of the robotic platform by assessing their muscle activation in real time. This type of feedback could benefit patients in learning more quickly how to activate robot functions, increasing their motivation towards rehabilitation.