Search Results (66)

This paper proposes a novel hierarchical control architecture that combines Model Predictive Control (MPC) with Explicit Model-Following Control (EMFC) to enable accurate and efficient trajectory tracking for quadrotor electric Vertical Takeoff and Landing (eVTOL) aircraft operating in urban environments. The approach addresses the challenges of strong nonlinear dynamics, multi-axis coupling, and stringent safety constraints by separating the planning task from the fast-response control task. The MPC layer generates constrained velocity and yaw rate commands based on a simplified inertial prediction model, effectively reducing computational complexity while accounting for physical and operational limits. The EMFC layer then compensates for dynamic couplings and ensures the rapid execution of commands. A high-fidelity simulation model, incorporating rotor flapping dynamics, differential collective pitch control, and enhanced aerodynamic interference effects, is developed to validate the controller. Four representative ADS-33E-PRF tasks—Hover, Hovering Turn, Pirouette, and Vertical Maneuver—are simulated. Results demonstrate that the proposed controller achieves accurate trajectory tracking, stable flight performance, and full compliance with ADS-33E-PRF criteria, highlighting its potential for autonomous urban air mobility applications. Full article

The accuracy of the blade pitch angle (BPA) motion in controllable pitch propellers (CPPs) is considered crucial for the efficacy and reliability of marine propulsion systems. The pitch adjustment process of CPPs is highly complex and influenced by various uncertain factors. A parametric kinematic model for the pitch adjustment process for CPPs was established, incorporating the geometric dimensions and material surface friction coefficients caused during workpiece production as uncertainty parameters. The aim was to establish the correspondence between these uncertainty parameters and the BPA of CPPs. A large dataset was generated by batch calling on Adams. Based on the collected dataset, five surrogate models (e.g., deep neural network (DNN), Kriging, support vector regression (SVR), random forest (RF), and polynomial chaos expansion Kriging (PCK)) were constructed to predict the BPA. Among these, the DNN approach demonstrated the highest prediction accuracy. Accordingly, the influence of uncertainties on the BPA was investigated using the DNN model, focusing on variations in the slider width, crank pin diameter, crank disc diameter, piston rod–slider friction coefficient, crank pin–slider friction coefficient, and hub bearing–crank disc friction coefficient. The high-fidelity model established in this study can replace the kinematic model of the CPP pitch adjustment process, significantly improving computational efficiency. The research findings also provide important references for the design optimization of CPPs. Full article

Wind turbines align with the wind direction and adjust to wind speed by rotating their nacelle and blades using electromechanical or hydraulic actuators. Due to the fact that the rated capacity of wind turbines is increasing and that the actuators are reaching some size limits, the current solution is to install several actuators at each joint until the required torque is reached. The problem with this approach is that, despite the fact the actuators can be selected from the same type and series, they typically have distinct parameters, resulting in different behaviours. The synchronisation of actuators of wind turbines has still not been studied in the specialised literature. Therefore, a control approach for the synchronisation of the pitch actuators is proposed in this work. Two cases are considered: the synchronisation of torque outputs and the synchronisation of position angle. The simulation results indicate that the proposed solution is effective for synchronising actuators, either when they are placed together on the same blade or when they are on separate blades while simultaneously following the collective pitch control command. Full article

A newly designed tilt-wing unmanned aerial vehicle (Tilt-wing UAV) requires a unified control strategy across rotary-wing, fixed-wing, and transition modes, introducing significant challenges. Existing control strategies typically rely on accurate modeling or extensive parameter tuning, which limits their adaptability to dynamically changing flight configurations. Although online reinforcement learning algorithms offer adaptability, they depend on real-world exploration, posing considerable safety and cost risks for safety-critical UAV applications. To address this challenge, we propose Temporal Sequence Constrained Q-learning (TSCQ), an offline RL framework that integrates an encoder–decoder with recurrent networks to capture temporal dependencies. The policy is further constrained within an offline dataset collected via hardware-in-the-loop simulation using a variational autoencoder, and a sequence-level prediction mechanism is introduced to ensure temporal consistency across action trajectories, thereby mitigating extrapolation error while preserving data fidelity. Experimental results demonstrate that TSCQ significantly outperforms gain scheduling, Model Predictive Control (MPC), and Batch-Constrained Q-learning (BCQ), reducing the RMSE of pitch angle by up to 53.3% and vertical velocity RMSE by approximately 33%. These findings underscore the potential of data-driven, safety-aware offline RL paradigms to enable robust and generalizable control strategies for tilt-wing UAVs. Full article

Miniscrews are used in orthodontic treatment and can be applied immediately after implantation, making their initial stability crucial. However, clinical reports show that the success rate is not 100%, and many researchers have tried to identify the factors influencing success and optimize designs. A review of the literature reveals that studies on the same geometric parameter of miniscrews using different indicators and different brand samples have led to conflicting results. This study will use consistent miniscrew conditions to verify whether the design differences in the literature are reasonable. This study employs the Taguchi method and ANOVA for optimization analysis. The four control factors comprise thread pitch, thread depth, tip taper angle, and self-tapping notch. Using an L9(3⁴) orthogonal array, the experimental models are reduced to nine. The primary stability indicators for the miniscrew include bending strength, pull-out strength, insertion torque, and self-tapping performance. The results of the single-objective experiments in this study align with the findings from the other literature. However, when analyzed collectively, they do not yield the same optimal solution. Under equal weighting, the combined multi-objective optimal solution is A2B2C1D1. This study exhibits minimal experimental error, ensuring high analytical reliability. The findings confirm that the optimal design does not converge across four single-objective analyses, as different stability indicators yield contradictory trends in design parameters. Given that these four indicators already demonstrate notable discrepancies, the influence of additional stability factors would be even more pronounced. Therefore, a multi-objective optimization approach is essential for the rational design of miniscrews. Full article

This work presents an in-depth study on the system identification of a servo-valve controlled hydraulic cylinder operating under variable load. This research addresses the growing demand for improved control systems (enhancing time response, settling time, and precision) in variable load hydraulic actuators, such as those used in blade pitching systems of wind turbines. The paper begins by detailing the experimental setup, followed by the development of the system’s mathematical model, a fourth-order transfer function (TF). The experimental data collected by a proposed data acquisition system are used for the dynamic identification of the hydraulic setup using periodical signals as commands. All possible combinations of TFs up to order 8 are identified. After an initial visual preselection of the 15 most accurate ones, analyses comparing quality indicators between the measured (experimental) and the TF (simulated) step and sinusoidal responses are conducted to determine the most accurate TF. The paper concludes with the presentation and analysis of the dynamic model, identified as being a fourth-order TF, which replicates the system dynamics with the greatest fidelity. It provides an identification methodology with significant potential for industry practitioners aiming to improve, optimize, and enhance control strategies for variable load hydraulic actuators. Full article

The optimization of the efficiency of wind turbine systems is a fundamental task, from the perspective of a growing share of electricity produced from wind. Despite this, and given the complex multivariate dependence of the power of wind turbines on environmental conditions and working parameters, the literature is lacking studies specifically devoted to a careful characterization of wind farm performance. In particular, in the literature, it is overlooked that there are several types of faults which have similar manifestations and that can be defined as static errors. This kind of error manifests as a static bias occurring from a certain time onward, which can affect the anemometer, the absolute or relative pitch of the blades, or the yaw system. Static or systematic errors typically do not cause the functional failure of the wind turbine system, but they deserve attention due to the fact that they cause power production loss throughout the operation time. Based on this, the first objective of the present study is a critical review of the recent papers devoted to three types of wind turbine static errors: anemometer bias, static yaw error, and pitch misalignment. As a result, a comprehensive viewpoint, enhancing the state of the art in the literature, is developed in this study. Given that the use of data collected by Supervisory Control And Data Acquisition (SCADA) systems has, up to now, been prevailing for the diagnosis of systematic errors compared to the use of further specific sensors, particular attention in the present study is thus devoted to the discussion of the phenomena which can be observable through SCADA data analysis. Based on this, finally, a rigorous work flow is formulated for detecting static errors and discriminating among them through SCADA data analysis. Nevertheless, methods based on additional information sources (like further sensors or meteorological data) are also discussed. An important aspect of this study is that, for each considered type of systematic error, some previously unpublished results based on real-world SCADA data are reported in order to corroborate the proposed framework. Summarizing, then, the present is the first paper which considers and discusses several types of wind turbine static errors in a unified viewpoint, correctly interprets apparently controversial results collected in the literature, and finally provides guidelines for the diagnosis of this kind of error and for the quantification of the performance drop associated with their presence. Full article

This contribution examines the control problem for very large wind energy converters during shutdown operation and analyses the most important control approaches. The control methods make use of the built-in conventional control infrastructure, but control system reconfigurations are undertaken in order to meet the demands of the shutdown control operation. Hence, the torque controller as well as the collective pitch controller (CPC) are redesigned from their regulator functions to reference tracking control systems with constraints. In addition, the CPC is combined with a feedforward controller in order to gain responsiveness. Constraints in magnitude and rate are managed by a modified anti-windup mechanism. Simulations of a 20 MW reference wind turbine verify the performance of the approaches. Full article

Wind turbines experience significant unbalanced loads during operation, exacerbated by external disturbances that challenge the stability of the pitch control system and affect output power. This paper proposes an independent pitch adaptive control strategy integrating state feedback and disturbance accommodating control (DAC). Initially, nonlinear wind turbine dynamics are globally linearized, and DAC is applied to mitigate the impact of wind disturbances dynamically. Subsequently, the entire range of wind speeds is segmented, and controllers are individually designed to optimize gain settings according to specific control objectives at each wind speed interval. Scheduling parameters such as collective pitch angle and tower fore-aft displacement are identified and trained using Radial Basis Function Neural Networks (RBFNN). Finally, based on the output gain values determined by RBFNN, the full-state feedback controller group is adaptively adjusted, and the optimal controller is selected for the final output. Simulations conducted on the NREL 5MW reference wind turbine model using FAST and Simulink demonstrate that compared to the ROSCO controller, the proposed strategy ensures smoother output power and effectively reduces blade and tower loads, thereby extending the turbine’s operational lifespan. Full article

Metaheuristic algorithms are computational techniques based on the collective behavior of swarms and the study of organisms acting in communities. These algorithms involve different types of organisms. Finding controller values for nonlinear systems is a challenging task using classical approaches. Hence, using metaheuristics to find the controller values of a twin rotor multi-input multi-output system (TRMS), one of the nonlinear systems studied in the literature, seems to be more appropriate than using classical methods. In this study, different types of metaheuristic algorithms were used to find the PID controller values for a TRMS, including a genetic algorithm (GA), a dragonfly algorithm, a cuckoo algorithm, a particle swarm optimization (PSO) algorithm, and a coronavirus optimization algorithm (COVIDOA). The obtained graphs were analyzed based on certain criteria for the main rotor and tail rotor angles to reach the reference value in the TRMS. The experimental results show that when the rise and settlement times of the TRMS are compared in terms of performance, the GA took 1.5040 s (seconds) and the COVIDOA took 9.59 s to increase the pitch angle to the reference value, with the GA taking 0.7845 s and the COVIDOA taking 2.4950 s to increase the yaw angle to the reference value. For the settling time, the GA took 11.67 s and the COVIDOA took 28.01 s for the pitch angle, while the GA took 14.97 s and the COVIDOA took 26.69 s for the yaw angle. With these values, the GA and COVIDOA emerge as the foremost algorithms in this context. Full article

Background: This study validates real-time biofeedback for lumbopelvic control training in baseball. The lumbopelvic region is crucial for generating kinetic energy in pitching. Real-time biofeedback enhances training effectiveness and reduces injury risk. The validity and reliability of this system were examined. Purpose: This study was to investigate the validity and reliability of the real-time biofeedback system for lumbopelvic control training. Methods: Twelve baseball players participated in this study, with data collected in two sessions separated by a week. All participants needed to do the lateral slide exercise and single-leg squat exercise in each session. Pelvic angles detected by the real-time biofeedback system were compared to the three-dimensional motion capture system (VICON) during training sessions. Additionally, pelvic angles measured by the biofeedback system were compared between the two training sessions. Results: The real-time biofeedback system exhibited moderate to strong correlations with VICON in both exercises: lateral slide exercise (r = 0.66–0.88, p < 0.05) and single-leg squat exercise (r = 0.70–0.85, p < 0.05). Good to excellent reliability was observed between the first and second sessions for both exercises: lateral slide exercise (ICC = 0.76–0.97) and single-leg squat exercise (ICC = 0.79–0.90). Conclusions: The real-time biofeedback system for lumbopelvic control training, accurately providing the correct pelvic angle during training, could enhance training effectiveness. Full article

This study explored how the Lombard effect, a natural or artificial increase in speech loudness in noisy environments, can improve speech-in-noise communication. This study consisted of several experiments that measured the impact of different types of noise on synthesizing the Lombard effect. The main steps were as follows: first, a dataset of speech samples with and without the Lombard effect was collected in a controlled setting; then, the frequency changes in the speech signals were detected using the McAulay and Quartieri algorithm based on a 2D speech representation; next, an average formant track error was computed as a metric to evaluate the quality of the speech signals in noise. Three image assessment methods, namely the SSIM (Structural SIMilarity) index, RMSE (Root Mean Square Error), and dHash (Difference Hash) were used for this purpose. Furthermore, this study analyzed various spectral features of the speech signals in relation to the Lombard effect and the noise types. Finally, this study proposed a method for automatic noise profiling and applied pitch modifications to neutral speech signals according to the profile and the frequency change patterns. This study used an overlap-add synthesis in the STRAIGHT vocoder to generate the synthesized speech. Full article

It is of great importance to simultaneously stabilize output power and suppress platform motion and fatigue loads in floating offshore wind turbine control systems. In this paper, a novel composite blade pitch control scheme considering actuator fault is proposed based on an augmented linear quadratic regulator (LQR), a fuzzy proportional integral (PI) and an adaptive second-order sliding-mode observer. Collective pitch control was achieved via the fuzzy PI, while individual pitch control was based on the augmented LQR. In the case of actuator fault, an adaptive second-order sliding-mode observer was constructed to effectively eliminate the need for the upper bound of unknown fault derivatives and suppress the chattering effect. This paper conducted co-simulations based on FAST (Fatigue, Aerodynamics, Structures, and Turbulence) and MATLAB/Simulink to verify the effectiveness and superiority of the proposed scheme under different environmental conditions. It is shown that platform roll was reduced by approximately 54% compared to that under PI control. For the tower fore–aft moment, load reductions of 45% or more were achievable. The proposed scheme can greatly reduce the pitch and roll of the floating platform and loads in the windward direction of the wind turbine. Full article

Little work has examined the L2 acquisition of Spanish stress, and especially the production of its acoustic correlates, and the work that has is largely limited to inexperienced learners. This study examines the production of stress by L1 English/L2 Spanish speakers who are highly experienced with their L2, having lived much of their adult lives as immigrants in Spain. Data were collected from the reading of a short story, an extended reading with a plot was provided so that participants would not be focused on their pronunciation, thus producing speech closer to spontaneous speech while still allowing for control over what they produced. Intensity, duration, pitch and deaccenting were examined and the results from the L2 learners were compared to a control group of native speakers from Spain who performed the same task. While only one L2 learner’s stress production could be classified as completely native-like, as a group, their stress production approximated native speaker norms to a greater degree than has been found for most other aspects of L2 Spanish pronunciation in previous research. Nonetheless, L2 learners seemed to transfer duration patterns from their L1 into their L2 Spanish and also deaccented stressed syllables nearly twice as often as native speakers. Full article

This paper studies the pilot control strategy and workload of a tilt-rotor aircraft dynamic conversion procedure between helicopter mode and fixed-wing mode. A nonlinear flight dynamics model of tilt-rotor aircraft with full flight modes is established. On this basis, a nonlinear optimal control model of dynamic conversion is constructed, considering factors such as conversion corridor limitations, pilot control, flight attitude, engine rated power, and wing stall effects. To assess pilot workload, an analytical method based on wavelet transform is proposed, which examines the mapping relationship between pilot control input amplitude, constituent frequencies, and control tasks. By integrating the nonlinear optimal control model and the pilot workload evaluation method, an analysis of the pilot control strategy and workload during the conversion procedure is conducted, leading to the identification of strategies to reduce pilot workload. The results indicate that incorporating the item of pilot workload in the performance index results in a notable reduction in the magnitude of collective stick inputs and longitudinal stick inputs. Moreover, it facilitates smoother adjustments in altitude and pitch attitude. Additionally, the conversion of the engine nacelle can be achieved at a lower and constant angular velocity. In summary, the conversion and reconversion procedures are estimated to have a low workload (level 1~2), with relatively simple and easy manipulation for the pilot. Full article