Search Results (108)

Floating offshore wind turbines (FOWTs) unlock superior wind resources and reduce operational barriers. The dynamics of FOWT platforms present added engineering challenges and opportunities. While the motion of the floating platform due to wind and wave disturbances can worsen power quality and increase structural loading, certain movements of the floating platform can be exploited to improve power capture. Consequently, active FOWT platform control methods using conventional and innovative actuation systems are under investigation. This paper develops a novel framework to design nonlinear control laws for six degrees-of-freedom platform motion. The framework uses simplified rigid-body analytical models of the FOWT. Lyapunov’s direct method is used to develop actuator-agnostic unconstrained control laws for platform translational and rotational control. A model based on the NREL-5MW reference turbine on the OC3-Hywind spar-buoy platform is utilized to test the control framework for an ideal actuation scenario. Possible applications using traditional and novel turbine actuators and future research directions are presented. Full article

This paper presents the development of a compact nanopositioning stage with long-range capabilities and six-degree-of-freedom (DOF) closed-loop control. The system, referred to as NPS6D100, provides Ø100 mm planar and 10 mm vertical travel range while maintaining direct force transfer to the moving platform (or slider) in all DOFs. Based on an integrated planar direct drive concept, the system is enhanced by precise vertical actuation and full 6D output feedback control. The mechanical structure, drive architecture, guiding, and measurement subsystems are described in detail, along with experimental results that confirm sub-10 nm servo errors under constant setpoint operation and in synchronized multi-axis motion scenarios. With its scalable and low-disturbance design, the NPS6D100 is well suited as a nanopositioning platform for sub-10 nm applications in nanoscience and precision metrology. Full article

This paper addresses the trajectory tracking control problem of a six-degree-of-freedom Gough–Stewart Platform (GSP) by proposing a control strategy that combines a sliding mode (SM) controller with a rapid forward kinematics solution algorithm. The study first develops an efficient forward kinematics method that integrates Support Vector Regression (SVR) with the Levenberg–Marquardt algorithm, effectively resolving issues related to multiple solutions and local optima encountered in traditional iterative approaches. Subsequently, a SM controller based on the GSP’s dynamic model is designed to achieve high-precision trajectory tracking. The proposed control strategy’s robustness and effectiveness are validated through simulation experiments, demonstrating superior performance in the presence of model discrepancies and external disturbances. Comparative analysis with traditional PD controllers and linear SM controllers shows that the proposed method offers significant advantages in both tracking accuracy and control response speed. This research provides a novel solution for high-precision control in GSP applications. Full article

In order to solve the problems of low efficiency and insufficient accuracy of the traditional manual template method in the forming detection of shell plates, a digital solution based on laser scanning detection system was proposed. By introducing a six-degree-of-freedom robotic arm and a high-precision line laser sensor to build a three-dimensional detection platform, a digital template method framework including data acquisition, point cloud registration, surface reconstruction, and deviation analysis was innovatively constructed. A point cloud non-penetration registration algorithm fused with boundary geometric information was proposed. Based on the improved Delaunay triangulation algorithm, the surface is reconstructed and the digital template is extracted. Experimental verification shows that the method achieves an accuracy of less than 1 mm of error in the detection of outer plates, shortens the single detection time to less than 10 min, and improves the detection efficiency by more than 75% compared with the traditional method. Full article

The Stewart-platform-based bumper plays a critical role in shipborne strap-down inertial navigation systems (SINSs), effectively mitigating shock-induced disturbances to ensure measurement accuracy. Dynamic modeling for the bumper under a huge impact is a key issue in predicting the shock isolation performance of the bumper. In this paper, the dynamic modeling of shock isolation performance for Stewart-platform-based bumpers under huge impacts is proposed and validated experimentally. Firstly, a model of a Stewart-platform-based bumper is established considering the geometric configuration and dynamic parameters of the bumper by calculating the Jacobian matrix, stiffness matrix, damping matrix and mass matrix. Secondly, an analytic simulation of the impact is presented based on the measured impact acceleration, and the impact force on the load is derived according to the non-displacement assumption in the impact stage. Then, the Lagrangian formulation was systematically applied to establish governing equations characterizing the six-degree-of-freedom (DOF) dynamics of the bumper, incorporating both inertial coupling effects and nonlinear shock energy dissipation mechanisms. Afterwards, dynamic equations were solved via the Runge–Kutta method to obtain the theoretical results. Finally, the proposed dynamic modeling and shock isolation performance analysis method was validated via impact experiments for the bumper. Full article

This study presents an automated docking block placement system developed for regular and emergency repairs of large ships and naval vessels. Traditional methods involve manually arranging heavy concrete docking blocks using cranes or forklifts, which can take several days and pose significant safety risks because of the heavy materials involved. The proposed system integrates an unmanned crane with a six-degree-of-freedom (6-DOF) robotic platform and a mobile robot-based 3D precision positioning system to automate block relocation. The use of a 3D laser tracker mounted on the mobile robot is the key to the system, which, when combined with environmental sensors such as LiDAR and RTK-GPS, provides millimeter-level positional feedback. To address the lack of clear reference points in conventional docking blocks, a precisely machined aluminum target block was attached to each block. An algorithm employing Density-Based Spatial Clustering of Applications with Noise (DBSCAN), KD-Tree, and Random Sample Consensus (RANSAC) techniques was used to detect and classify the vertex of the target block from the 3D point cloud data. The experimental results demonstrated a positional measurement error within 0.5 mm at an 8 m distance. This novel system reduces the setup time, enhances worker safety, and increases the overall efficiency and capacity of dry dock maintenance operations. Full article

This paper proposes an enhanced RRT* algorithm (XN-RRT*) to address the challenges of low path planning efficiency and suboptimal picking success rates in complex pitaya harvesting environments. The algorithm generates sampling points based on normal distribution and dynamically adjusts the center and range of the sampling distribution according to the target distance and tree density, thus reducing redundant sampling. An improved artificial potential field method is employed during tree expansion, incorporating adjustment factors and target points to refine the guidance of sampling points and overcome local optima and infeasible targets. A greedy algorithm is then used to remove redundant nodes, shorten the path, and apply cubic B-spline curves to smooth the path, improving the stability and continuity of the robotic arm. Simulations in both two-dimensional and three-dimensional environments demonstrate that the XN-RRT* algorithm performs effectively, with fewer iterations, high convergence efficiency, and superior path quality. The simulation of a six-degree-of-freedom robotic arm in a pitaya orchard environment using the ROS2 platform shows that the XN-RRT* algorithm achieves a 98% picking path planning success rate, outperforming the RRT* algorithm by 90.32%, with a 27.12% reduction in path length and a 14% increase in planning success rate. The experimental results confirm that the proposed algorithm exhibits excellent overall performance in complex harvesting environments, offering a valuable reference for robotic arm path planning. Full article

The foundation structure of offshore substation platforms is complex and has numerous degrees of freedom. The computational efficiency of dynamic response analysis using traditional time-domain methods is often relatively low. To facilitate the dynamic response analysis of offshore substation platform foundation structures with large degrees of freedom (DOFs), this paper proposes a method for dynamic response analysis based on modal truncation, which involves conducting a modal analysis and decoupling the vibration system matrix based on the modal shapes. Additionally, it analyzes the external load spectrum and determines the modal-truncation range through the transfer relationship between the external load frequency and the modal response. This approach reduces the size of the dynamic response analysis matrix, thereby significantly improving the computational efficiency of the dynamic response analysis of large-DOF offshore substation platform foundations. A six-DOF mass-damping-spring system and a finite element model of an offshore substation platform foundation were used to test the proposed method. The proposed method reduces the number of decoupled equations used to analyze the offshore substation platform foundation from 312 to 9. It was compared with the Newmark-β method, and the results show that the proposed method aligns well with the Newmark-β method in terms of calculation results, with computational efficiency improved by approximately 100 times. Full article

Changes in the flight attitude of plant protection unmanned aerial vehicles (UAVs) can lead to oscillations in the liquid level of their medicine tanks, which may affect operational accuracy and stability, and could even pose a threat to flight safety. To address this issue, this article presents the design of a flight attitude simulator for crop protection UAVs, constructed on a six-degree-of-freedom motion platform. This simulator can replicate the various flight attitudes, such as emergency stops, turns, and point rotations, of plant protection UAVs. This article initially outlines the determination and design process for the structural parameters and 3D model of the flight attitude simulator specific to plant protection UAVs. Subsequently, simulations were performed to analyze liquid sloshing in the pesticide tank under various liquid flushing ratios during flight conditions, including emergency stops, climbs, and circling maneuvers. Finally, the influence of liquid sloshing on the flight stability of the plant protection UAVs in different attitudes and with varying liquid flushing ratios is presented. These results serve as a cornerstone for optimizing the flight parameters of plant protection UAVs, analyzing the characteristics of pesticide application, and designing effective pesticide containers. Full article

The forward kinematics of the Stewart platform is crucial for precise control and reliable operation in six-degree-of-freedom motion. However, there are some shortcomings in practical applications, such as calculation precision, computational efficiency, the capacity to resolve singular Jacobian matrix and real-time predictive performance. To overcome those deficiencies, this work proposes a hybrid strategy for forward kinematics in the Stewart platform based on dual quaternion neural network and ARMA time series prediction. This method initially employs a dual-quaternion-based back-propagation neural network (DQ-BPNN). The DQ-BPNN is partitioned into real and dual parts, composed of parameters such as driving-rod lengths, maximum and minimum lengths, to extract more features. In DQ-BPNN, a residual network (ResNet) is employed, endowing DQ-BPNN with the capacity to capture deeper-level system characteristics and enabling DQ-BPNN to achieve a better fitting effect. Furthermore, the combined modified multi-step-size factor Newton downhill method and the Newton–Raphson method (C-MSFND-NR) are employed. This combination not only enhances computational efficiency and ensures global convergence, but also endows the method with the capability to resolve a singular matrix. Finally, a traversal method is adopted to determine the order of the autoregressive moving average (ARMA) model according to the Bayesian information criterion (BIC). This approach efficiently balances computational efficiency and fitting accuracy during real-time motion. The simulations and experiments demonstrate that, compared with BPNN, the R² value in DQ-BPNN increases by 0.1%. Meanwhile, the MAE, MAPE, RMSE, and MSE values in DQ-BPNN decrease by 8.89%, 21.85%, 6.90%, and 3.3%, respectively. Compared with five Newtonian methods, the average computing time of C-MSFND-NR decreases by 59.82%, 83.81%, 15.09%, 79.82%, and 78.77%. Compared with the linear method, the prediction accuracy of the ARMA method increases by 14.63%, 14.63%, 14.63%, 14.46%, 16.67%, and 13.41%, respectively. Full article

With the increasing global emphasis on sustainable energy, wave energy has gained recognition as a significant renewable marine resource, drawing substantial research attention. However, the efficient conversion of low-frequency, random, and low-energy wave motion into electrical power remains a considerable challenge. In this study, an advanced hybrid generator design is introduced which enhances wave energy harvesting by optimizing wave–body coupling characteristics and incorporating both a triboelectric nanogenerator (TENG) and an electromagnetic generator (EMG) within the shell. The optimized asymmetric trapezoidal shell (ATS) improves output frequency and energy harvesting efficiency in marine environments. Experimental findings under simulated water wave excitation indicate that the accelerations in the x, y, and z directions for the ATS are 1.9 m·s⁻², 0.5 m·s⁻², and 1.4 m·s⁻², respectively, representing 1.2, 5.5, and 2.3 times those observed in the cubic shell. Under real ocean conditions, a single TENG unit embedded in the ATS achieves a maximum transferred charge of 1.54 μC, a short-circuit current of 103 μA, and an open-circuit voltage of 363 V, surpassing the cubic shell by factors of 1.21, 1.24, and 2.13, respectively. These performance metrics closely align with those obtained under six-degree-of-freedom platform oscillation (0.4 Hz, swing angle range of ±6°), exceeding the results observed in laboratory-simulated waves. Notably, the most probable output frequency of the ATS along the x-axis reaches 0.94 Hz in ocean trials, which is 1.94 times the significant wave frequency of ambient sea waves. The integrated hybrid generator efficiently captures low-quality wave energy to power water quality sensors in marine environments. This study highlights the potential of combining synergistic geometric shell design and generator integration to achieve high-performance wave energy harvesting through improved wave–body coupling. Full article

The main task of the research involves creating a Digital Twin (DT) application serving as a framework for Virtual Commissioning (VC) with Supervisory Control and Data Acquisition (SCADA) and Cloud storage solutions. An Internet of Things (IoT) integrated automation system with Virtual Private Network (VPN) remote control for assembly and disassembly robotic cell (A/DRC) equipped with a six-Degree of Freedom (6-DOF) ABB 120 industrial robotic manipulator (IRM) is presented in this paper. A three-dimensional (3D) virtual model is developed using Siemens NX Mechatronics Concept Designer (MCD), while the Programmable Logic Controller (PLC) is programmed in the Siemens Totally Integrated Automation (TIA) Portal. A Hardware-in-the-Loop (HIL) simulation strategy is primarily used. This concept is implemented and executed as part of a VC approach, where the designed PLC programs are integrated and tested against the physical controller. Closed loop control and RM inverse kinematics model are validated and tested in PLC, following HIL strategy by integrating Industry 4.0/5.0 concepts. A SCADA application is also deployed, serving as a DT operator panel for process monitoring and simulation. Cloud data collection, analysis, supervising, and synchronizing DT tasks are also integrated and explored. Additionally, it provides communication interfaces via PROFINET IO to SCADA and Human Machine Interface (HMI), and through Open Platform Communication—Unified Architecture (OPC-UA) for Siemens NX-MCD with DT virtual model. Virtual A/DRC simulations are performed using the Synchronized Timed Petri Nets (STPN) model for control strategy validation based on task planning integration and synchronization with other IoT devices. The objective is to obtain a clear and understandable representation layout of the A/DRC and to validate the DT model by comparing process dynamics and robot motion kinematics between physical and virtual replicas. Thus, following the results of the current research work, integrating digital technologies in manufacturing, like VC, IoT, and Cloud, is useful for validating and optimizing manufacturing processes, error detection, and reducing the risks before the actual physical system is built or deployed. Full article

With the urgent demand for net-zero emissions, renewable energy is taking the lead and wind power is becoming increasingly important. Among the most promising sources, offshore wind energy located in deep water has gained significant attention. This review focuses on the experimental methods, simulation approaches, and wake characteristics of floating offshore wind turbines (FOWTs). The hydrodynamics and aerodynamics of FOWTs are not isolated and they interact with each other. Under the environmental load and mooring force, the floating platform has six degrees of freedom motions, which bring the changes in the relative wind speed to the turbine rotor, and furthermore, to the turbine aerodynamics. Then, the platform’s movements lead to a complex FOWT wake evolution, including wake recovery acceleration, velocity deficit fluctuations, wake deformation and wake meandering. In scale FOWT tests, it is challenging to simultaneously satisfy Reynolds number and Froude number similarity, resulting in gaps between scale model experiments and field measurements. Recently, progress has been made in scale model experiments; furthermore, a “Hardware in the loop” technique has been developed as an effective solution to the above contradiction. In numerical simulations, the coupling of hydrodynamics and aerodynamics is the concern and a typical numerical simulation of multi-body and multi-physical coupling is reviewed in this paper. Furthermore, recent advancements have been made in the analysis of wake characteristics, such as the application of instability theory and modal decomposition techniques in the study of FOWT wake evolution. These studies have revealed the formation of vortex rings and leapfrogging behavior in adjacent helical vortices, which deepens the understanding of the FOWT wake. Overall, this paper provides a comprehensive review of recent research on FOWT wake dynamics. Full article

Industrial robotic arms are often subject to significant end-effector pose deviations from the target position due to the combined effects of nonlinear deformations such as link flexibility, joint compliance, and end-effector load. To address this issue, a study was conducted on the analysis and compensation of end-position errors in a six-degree-of-freedom robotic arm. The kinematic model of the robotic arm was established using the Denavit–Hartenberg (DH) parameter method, and a rigid–flexible coupled virtual prototype model was developed using ANSYS and ADAMS. Kinematic simulations were performed on the virtual prototype to analyze the variation in end-effector position errors under rigid–flexible coupling conditions. To achieve error compensation, an approach based on an Enhanced Crayfish Optimization Algorithm (ECOA) optimizing a BP neural network was proposed to compensate for position errors. An experimental platform was constructed for error measurement and validation. The experimental results demonstrated that the positioning accuracy after compensation improves by 75.77%, fully validating the effectiveness and reliability of the proposed method for compensating flexible errors. Full article

This paper presents the development of a virtual walker for wheelchair users designed for use in highly immersive environments, such as Cave Automatic Virtual Environments (CAVEs). The system allows users to navigate virtual environments using their natural wheelchair movements, providing haptic feedback based on the terrain they traverse. Both the control software and hardware have been developed from scratch and integrated into various CAVEs, including one with a six-degree-of-freedom (DOF) motion platform. To test the system, a comparative study was conducted with 21 users, measuring the time taken to complete the same course using different interaction methods and various feedback configurations with the virtual environment. The results show that the shortest times were achieved when users navigated using their natural interaction with their wheelchairs. Full article