Angle Control Research Articles

Giant resistance switch in twisted transition metal dichalcogenide tunnel junctions

Abstract Resistance switching in multilayer structures are typically based on materials possessing ferroic orders. Here we predict an extremely large resistance switching based on the relative spin-orbit splitting in twisted transition metal dichalcogenide (TMD) monolayers tunnel junctions. Because of the valence band spin splitting which depends on the valley index in the Brillouin zone, the perpendicular electronic transport through the junction depends on the relative reciprocal space overlap of the spin-dependent Fermi surfaces of both layers, which can be tuned by twisting one layer. Our quantum transport calculations reveal a switching resistance larger than 106% when the relative alignment of TMDs goes from 0º to 60º and when the angle is kept fixed at 60º and the Fermi level is varied. By creating vacancies, we evaluate how inter-valley scattering affects the efficiency and find that the resistance switching remains large (104%) for typical values of vacancy concentration. Not only should this resistance switching be observed at room temperature due to the large spin splitting, but our results also show how twist angle engineering and control of van der Waals heterostructures could be used for next-generation memory and electronic applications.

Slip angle control based DTC of open-end winding induction motor drive using dual randomized decoupled PWM for acoustic noise mitigation in EV application

Slip angle control based DTC of open-end winding induction motor drive using dual randomized decoupled PWM for acoustic noise mitigation in EV application

Modified load angle direct torque control for dual star motor using fuzzy logic

Space Vector Modulation (SVM) has emerged as a prominent alternative for motor control, particularly within the framework of Direct Torque Control (DTC-SVM). SVM leverages variations in the load angle, which result from changes in motor torque, to generate the appropriate voltage vectors. The conventional approach to this method involves a single Proportional-Integral (PI) regulator, which is characterized by a constant switching frequency and the capability to reduce ripples in torque, flux, and current. Despite these advantages, the PI regulator may face challenges in maintaining optimal performance under varying load conditions. This study seeks to enhance the performance of the DTC-SVM strategy by integrating Fuzzy Logic into the PI regulator. The primary objective is to improve the accuracy and responsiveness of the load angle control, thereby optimizing the motor's operational efficiency. The proposed SVM-Fuzzy control scheme is designed to address the limitations of the traditional PI regulator, offering a more adaptive and robust solution for motor control. To evaluate the effectiveness of the proposed approach, extensive simulations were conducted using Matlab Simulink. The SVM-Fuzzy strategy was compared against the conventional SVM-PI approach to assess its performance in terms of torque, flux, and current regulation. The SVM-Fuzzy control scheme significantly enhances efficiency, stability, and load angle precision, particularly in Double Star Induction Motors (DSIM). It also ensures the durability and reliability of the motor control system under different operating conditions.

Online Safe Flight Control Method Based on Constraint Reinforcement Learning

UAVs are increasingly prominent in the competition for space due to their multiple characteristics, such as strong maneuverability, long flight distance, and high survivability. A new online safe flight control method based on constrained reinforcement learning is proposed for the intelligent safety control of UAVs. This method adopts constrained policy optimization as the main reinforcement learning framework and develops a constrained policy optimization algorithm with extra safety budget, which introduces Lyapunov stability requirements and limits rudder deflection loss to ensure flight safety and improves the robustness of the controller. By efficiently interacting with the constructed simulation environment, a control law model for UAVs is trained. Subsequently, a condition-triggered meta-learning online learning method is used to adjust the control raw online ensuring successful attitude angle tracking. Simulation experimental results show that using online control laws to perform aircraft attitude angle control tasks has an overall score of 100 points. After introducing online learning, the adaptability of attitude control to comprehensive errors such as aerodynamic parameters and wind improved by 21% compared to offline learning. The control law can be learned online to adjust the control policy of UAVs, ensuring their safety and stability during flight.

Robust PI-PD Controller Design: Industrial Simulation Case Studies and a Real-Time Application

PI-PD controllers have superior performance compared to traditional PID controllers, especially for controlling unstable and integrating industrial processes with time delays. However, computing the four tuning parameters of this type of controller is not an easy task. Recently, there has been significant interest in determining the tuning rules for PI-PD controllers that utilize the stability region. Currently, most tuning rules for the PI-PD controller are presented graphically, which can be time-consuming and act as a barrier to their industrial application. There is a lack of analytical tuning guidelines in the literature to address this shortfall. However, the existing analytical tuning guidelines do not consider a rigorous design approach. This work proposes new robust analytical tuning criteria based on predefined gain and phase margin bounds, as well as the centroid of the stability region. The proposed method has been tested using various simulation studies related to a DC–DC buck converter, a DC motor, and a heat exchanger. The results indicate that the proposed tuning rules exhibit strong performance against parameter uncertainty with minimal overshoots. Furthermore, the suggested technique for simultaneous control of yaw and pitch angles has been tested in a real-time application using the twin rotor multi-input multi-output system (TRMS). Real-time results indicate that, compared to other methods under investigation, the suggested approach provides nearly minimal overshoots.

Innovative real-time deloading approach to wind systems with applications in primary frequency control

The integration of wind systems into the electrical grid faces a significant challenge due to the absence of inertia, a fundamental characteristic of this system. This lack of internal inertia directly impacts frequency stability. To address this challenge, various techniques have been developed, including storage systems, inertia emulation, and deloading methods, among others. Among these approaches, the latter method appears to be more suitable. This study introduces a novel deloading approach that offers several advantages. The proposed strategy is an online technique that is easy to implement. It does not necessitate mathematical models, estimations, prior knowledge of wind turbine (WT) characteristics, or the use of an extra sensor, thereby simplifying the approach. This approach is based on a WT cycle consisting of two consecutive operating modes: a maximum power measurement (MPM) mode and a power reserve (PR) mode. These modes are controlled by two controllers: a pitch angle controller (PAC) and a perturb and observe (P&O) algorithm controller. The cycle is managed and initiated using a monitoring signal with multiple configurations, providing various solutions and implementation possibilities. The effectiveness of this approach has been verified through numerous simulation tests conducted on both finite and isolated grids. These simulations employ theoretical and actual wind speed signals in the MATLAB Simulink environment, confirming the practicality and reliability of the proposed method.

Enhanced Conflict Avoidance and Dynamic Path Replanning for Multi-UAVs through MILP with Real-time Speed and Heading Angle Control

Enhanced Conflict Avoidance and Dynamic Path Replanning for Multi-UAVs through MILP with Real-time Speed and Heading Angle Control

Fast automatic docking control for electric tractors

In this study, we investigate the automatic docking of an electric tractor with a semi-trailer in narrow and long-distance scenarios. We propose an automatic docking method based on a multi-sensor fusion high-precision positioning algorithm and a multi-strategy docking control algorithm. To solve the heading-angle error of the involved camera due to mechanical errors, a compensation value in the form of angle deviation is introduced. To alleviate the increase in the camera detection error with longitudinal distance, a piecewise coordinate compensation function is proposed. Repositioning is performed using light detection and ranging (Lidar) to improve the pose-perception accuracy to the millimeter level. To avoid the interference of point clouds on the relocation accuracy of Lidar, a search-and-location method that combines both small and large neighborhoods is proposed. To achieve the desired docking success rate, a multi-strategy-adjustment control algorithm is used to enable comprehensive adjustment, including approximate control of the maximum angle based on lateral deviation and fine proportional-integral-differential (PID) control based on lateral deviation and longitudinal distance, security check cycle and premature warning mechanism, and risk avoidance control. Finally, the reliability and stability of the design scheme are verified by conducting multiple experiments involving actual vehicles.

The correlation analysis between incisal guidance angle and occlusal plane angles and temporomandibular joint morphology.

The correlations between the incisal guidance angle (IGA) and occlusal plane angles and temporomandibular joint (TMJ) morphology were investigated in adults with skeletal Class II division II malocclusion. CBCT images of 37 patients were analyzed. It included 19 cases of skeletal Class II division II malocclusion with low angle (study group) and 18 cases of skeletal Class I average angle (control group). The Invivo Dental 5 software was employed to acquire the data of the incisal guidance angle (IGA), occlusal plane angle (FH-OP), anterior occlusal plane angle (FH-AOP) and the TMJ measurement items. The results of IGA, FH-AOP angle and FH-OP angle showed the study group > the control group (P < 0.05). There were statistically difference in the condylar mediolateral diameters, articular eminence inclination and height, and posterior joint spaces between two groups. No differences were revealed in the condylar anteroposterior diameters, the condylar inclination angle, condylar head width and height, condylar length, glenoid fossa depth and width between two groups. In the study group, IGA showed a moderate correlation with FH-AOP, a weak correlation with FH-OP and condylar mediolateral diameters. Meanwhile, there was a correlation between FH-AOP, FH-OP, and TMJ indicators. The IGA was not only related to FH-AOP and FH-OP, but also to the condylar mediolateral diameters. In addition, there was a correlation between the occlusal plane angles and TMJ morphology in skeletal Class II division II low angle malocclusion. For patients with skeletal Class II division II low angle malocclusion, adjusting the IGA and the occlusal plane angles could improve the esthetic appearance of the anterior teeth, occlusal function, and TMJ morphology.

High-efficiency thermo-optic control of a longitudinal radiation angle in a silicon-based optical phased array by leveraging the backside air trench structure.

We proposed a 2D 1 × 64 silicon optical phased array with a backside silicon-etched structure to achieve high tuning efficiency and a wide longitudinal steering range. At the radiator array, the n-i-n heater was implemented to steer the light in a longitudinal direction through the thermo-optic effect. The deep reactive ion etching process was utilized to generate the 600 µm depth air trench with a 1.8 cm2 area from the backside of the radiator array. We achieved almost 100% increment in terms of tuning efficiency, which is 1.56°/W for the proposed structure and 0.78°/W for the conventional structure.

Stability and Controller Research of Double-Wing FMAV System Based on Controllable Tail.

This study aimed to enhance the stability and response speed of a passive stabilized double-wing flapping micro air vehicle (FMAV) by implementing a feedback-controlled biomimetic tail. A model for flapping wings accurately calculated the lift force with only a 2.4% error compared to the experimental data. Experimental tests established the relationship between control torque and tail area, swing angle, and wing-tail spacing. A stability model for the double-wing FMAV was developed, incorporating stabilizing sails. Linearization of the hovering state facilitated the design of a simulation controller to improve response speed. By adjusting the feedback loops of velocity, angle, and angular velocity, the tail controller reduced the angle simulation response time from 4 s to 0.1 s and the velocity response time from 5.64 s to 0.1 s. In take-off experiments, a passive stabilized prototype with an adjustable tail angle exhibited enhanced flight stability compared to fixed tails, reducing standard deviation by 72.96% at a 0° take-off angle and 56.85% at a 5° take-off angle. The control axis standard deviation decreased by 38.06% compared to the passive stability axis, confirming the effectiveness of the designed tail angle controller in reducing angular deflection and improving flight stability.

Optimal predictive voltage control of a wind driven five phase PMSG system feeding an isolated load

Wind energy conversion systems (WECS) are considered to be a promising alternative to traditional power generation systems. The principal purpose of this study is to enhance the performance of a stand-alone wind-driven five-phase PMSG system. The initial step involves providing a clear explanation of the system model, which includes the wind turbine, five-phase PMSG, and a battery storage system. Then, the maximum power point tracking (MPPT) and pitch angle control (PAC) technique is employed to optimize the power delivered to an isolated load. Furthermore, the system incorporates the machine-side converter (MSC) and battery converter, which require control to efficiently regulate the power delivered from them to an isolated load. In addition, the MSC is regulated by two predictive control algorithms: predictive torque control (PTC) and a newly formulated predictive voltage control (PVC). The PTC faces limitations such as considerable ripple, significant load commutation, and the weighting factor of its cost functions. The proposed prediction technique aims to overcome these constraints by using a simple cost function and eliminating the need for weighting factors to address stability issues also another study's objective revolves around proposing a PVC controller that achieves an optimal design. The results demonstrate that the newly proposed predictive controller outperforms the conventional control method for the wind generator. The developed controller produces consistently distributed sinusoidal currents with significantly fewer ripples and current harmonics. This fact is verified mathematically as the total harmonic distortion (THD) is reduced to 1.168 % as an average value.

Optimizing DFIG‐DC system performance via model predictive control: Torque ripple, DC voltage drop, and THD reduction

AbstractIn this study, two novel control methods are theoretically introduced as direct slip angle control (DSAC) and model predictive direct slip angle control (MPDSAC) for rotor side converter (RSC) of the standalone Doubly‐Fed Induction Generator (DFIG)‐DC system (S‐DFIG‐DC). The numerical analysis of the proposed methods demonstrated that the proposed DSAC method could reduce torque ripple and current harmonics, decrease the output DC voltage drop in fast changes of load condition, and have faster dynamic response. Also, the MPDSAC method could further diminish torque and flux ripple, current harmonics, and output DC voltage drop in sharp changes of load condition compared with the presented DSAC and direct torque control (DTC) methods. The sensitivity analysis of the proposed control methods is investigated at different operating conditions. The performance and usefulness of the DSAC and MPDSAC schemes are verified by various experiments and compared with the conventional DTC method.

A Novel Predictive Voltage Control Technique for a Grid Connected Five Phase Permanent Magnet Synchronous Generator

This study focuses on developing an effective control strategy to enhance the dynamics of a wind turbine grid-connected five-phase permanent magnet synchronous generator (PMSG). To visualize the superior performance of the newly proposed controller, the generator's performance is evaluated with another traditional predictive control scheme: predictive torque control (PTC). However, the vector control principle is applied to the GSC converter. The PTC has limitations such as significant ripple, substantial load commutation, and the inclusion of a weighting element in its cost functions. The proposed predictive methodology aims to overcome limitations, uses a simple cost function, and doesn't require weighting elements to address concerns about stability errors. Comparing the proposed predictive voltage controller (PVC) to the PTC, the findings show that the suggested PVC has many benefits, including faster dynamic response, a simpler control structure, fewer ripples, reduced current harmonics, low computation burdens, and robustness, so the generated power affects system efficiency, leading to improved power quality and reduced switching losses, enhancing power converters efficiency and their switches lifespan, this fact is verified mathematically as the total harmonic distortion (THD) has reduced to 1.346% average percentage for the proposed controller. However, the THD of the PTC is 3.05%. In addition, the study examines the incorporation of pitch angle control (PAC) and maximum power point tracking (MPPT). These controls restrict the consumption of wind energy when the generator speed surpasses its rated speed and optimize the extraction of wind energy during periods of low wind availability. In summary, the proposed PVC-enhanced control system reveals superior performance in dynamic response, control simplicity, current quality, and computational efficiency compared to other methods.

Impact of PLL and non-PLL vector current control techniques on grid connected inverter

In the micro-grids, all the Distributed Power Generation Systems (DPGS) and loads are interconnected across the Point of Common Coupling (PCC). The stability and harmonics of the grid connected inverters are significantly impacted by uncertainties in the renewable energy sources based DPGS. The performance of these grid connected inverters across the PCC depends on the Phase-Locked Loop (PLL) used to track the grid angle and power control structures used to control the power fed to grid. These power control structures can be either PLL based or PLL less systems. The PLL based Vector Current Control Direct Quadrature (VCC DQ) control and PLL less Non-PLL Vector Control (NPVC) techniques are compared along with their controller design and bode plots. Also, the small signal models of grid connected inverter with PLL are presented from which the converter impedance is derived to show the effect of PLL on the system using bode plots. The impact of the PLL based and PLL less control techniques on the grid connected inverter are presented with analytical equations along with simulation and hardware results. A 6 kW grid connected inverter simulation model and 150 W hardware prototype is developed using TI F28379D processor to compare the performance of both with and without PLL control techniques.

Constrained Maximum Power Extraction in PMVG Wind Turbine System With Predictive Rotor Position Bias-Based Current Angle Control for Power Factor Improvement

Constrained Maximum Power Extraction in PMVG Wind Turbine System With Predictive Rotor Position Bias-Based Current Angle Control for Power Factor Improvement

Data-Driven-Method-Based Guidance Law for Impact Time and Angle Constraints

To increase the hit efficiency and lethality of a flight vehicle, it is necessary to consider the vehicle’s guidance law concerning both impact time and angle constraints. In this study, a novel and straightforward impact time and angle control guidance law that is independent of time-to-go and small angle approximations is proposed with two stages using a data-driven method and proportional navigation guidance. First, a proportional navigation guidance-based impact angle control guidance law is designed for the second stage. Second, from various initial conditions on the impact angle control guidance simulation with various initial conditions, the input and output datasets are obtained to build a mapping network. Using the neural network technique, a mapping network model that can output the ideal flight path angle in flight is constructed for impact time control in the first stage. The proposed impact time and angle control guidance law reduces to the proportional navigation guidance law when the flight path angle error converges to zero. The simulation results show that the proposed guidance law delivers excellent performance under various conditions (including cooperative attack) and features better acceleration performance and less control energy than does the comparative impact time and angle control guidance law. The results of this research are expected to supplement those exploring various paradigms to solve the impact time and angle control guidance problem, as concluded in the current literature.

SIMULACIÓN AVANZADA DE UN BRAZO ROBÓTICO CON 2 GRADOS DE LIBERTAD, CONTROLADO EN SIMSCAPE

In this project, a robotic arm was developed, modeled, and implemented using the Matlab Simulink programming platform. The robotic arm was designed with 2 degrees of freedom and equipped with three motors, allowing for precise and coordinated control of its movements. For simulating the dynamic and kinematic behavior of the arm, Simscape blocks were used, facilitating a detailed three-dimensional representation of the system. The main objective of the project was to demonstrate a simulation of the robotic arm that allows for precise control of the movement angles. Through a detailed 3D simulation in Simscape, the movement and interaction of the arm's components could be visualized, validating its capability to perform tasks with high precision and efficiency. The results obtained demonstrate the effectiveness of using Simulink and Simscape in the design and simulation of robotic systems, highlighting the importance of these tools for automated development.

Anterior Chamber Angle and Intraocular Pressure Control After Phacoemulsification in Primary Angle Closure With Different Mechanisms.

Different mechanisms of angle closure represented distinct aspects of intraocular pressure (IOP) control after phacoemulsification. Classification of angle closure mechanisms is necessary for postoperative IOP management and glaucoma progression in primary angle closure eyes. To investigate the relationship between the anterior chamber angle (ACA) characteristics, measured by swept-source anterior segment optical coherence tomography (SS AS-OCT), and intraocular pressure (IOP) control after phacoemulsification in eyes with primary angle closure disease (PACD) with different angle closure mechanisms. PACD eyes were classified into 3 groups according to angle closure mechanisms using preoperative SS AS-OCT images; pupillary block (PB), plateau iris configuration (PIC), exaggerated lens vault (ELV). This retrospective, clinical cohort study included eighty-five eyes of 85 PACD patients: 34 with PB, 23 with PIC, and 28 with ELV. ACA parameters were measured preoperatively and 1 month postoperatively using SS AS-OCT. IOP measurements were performed preoperatively and during 6 months postoperatively. Postoperative IOP reduction and fluctuation were calculated, and their correlations with SS AS-OCT parameters were analyzed. PIC group showed the lowest postoperative IOP reduction compared with the other groups ( P =0.023). Preoperative ACA measurements were significantly associated with postoperative IOP reduction in ELV and PB groups, while postoperative measurements were in PIC group. Preoperative and postoperative change of iridotrabecular contact (ITC) index and area were correlated with postoperative IOP reduction in PB and ELV groups but not in PIC group. Postoperative ITC index ( P =0.031) and area ( P =0.003) showed significant correlations with postoperative IOP fluctuation only in PIC group. SS AS-OCT parameters including ITC index and area showed different associations with postoperative IOP control, which should be considered in determination of lens extraction and treatment of PACD eyes.

AN EXPERIMENTAL INVESTIGATION ON NOVEL SEGMENTED OMNI WHEELED HYBRID MOBILE ROBOT TO ASSESS OBSTACLE CLIMBING CAPABILITY

Abstract This article introduces a novel quadrupedal hybrid mobile robot with a segmented omni wheel design capable of climbing obstacles of height greater than its wheel radius. The unique wheel design comprises of two parallel coaxial 240-degree segmented omni wheels per leg with independent offset angle control. The transformation from wheel to leg mode and vice versa can be seamlessly achieved by controlling the offset angle between the segmented omni wheels. A series of experiments are carried out to evaluate the robot's performance for obstacle climbing capability utilizing various wheel end effector designs, and a comparative analysis is presented. The results indicate that the obstacle climbing capability of segmented omni wheel design with zero offset angle is improved by 40.7% compared to standard wheel and the unique wheel design configuration facilitates seamless staircase climbing capability without any complex control scheme. In addition, statistical studies using Taguchi method and ANOVA are performed on the experimental findings. A linear regression model to predict power consumption has been developed and the significant factors influencing the robot's power consumption and stability are presented.