Position Signal Research Articles

Optimal calibration of optical tweezers with arbitrary integration time and sampling frequencies: a general framework [Invited

Optical tweezers (OT) have become an essential technique in several fields of physics, chemistry, and biology as precise micromanipulation tools and microscopic force transducers. Quantitative measurements require the accurate calibration of the trap stiffness of the optical trap and the diffusion constant of the optically trapped particle. This is typically done by statistical estimators constructed from the position signal of the particle, which is recorded by a digital camera or a quadrant photodiode. The finite integration time and sampling frequency of the detector need to be properly taken into account. Here, we present a general approach based on the joint probability density function of the sampled trajectory that corrects exactly the biases due to the detector's finite integration time and limited sampling frequency, providing theoretical formulas for the most widely employed calibration methods: equipartition, mean squared displacement, autocorrelation, power spectral density, and force reconstruction via maximum-likelihood-estimator analysis (FORMA). Our results, tested with experiments and Monte Carlo simulations, will permit users of OT to confidently estimate the trap stiffness and diffusion constant, extending their use to a broader set of experimental conditions.

Variable-gain sliding mode control for quadrotor vehicles: Lyapunov-based analysis and finite-time stability

This work presents a methodology for controlling a quadrotor vehicle in both regulation and trajectory tracking tasks when the system is affected by endogenous and exogenous disturbances. In the proposed approach, the quadrotor is driven by a second-order variable-gain sliding mode controller (VG-SMC), which includes a state-dependent variable-gain that allows enhancing the controller performance against disturbances. Besides, the proposed controller achieves finite-time convergence of the position and orientation error signals and their time derivatives. The performance of the closed-loop system is assessed by comparing it with a standard sliding mode controller whose control objective is to track two optimal smooth reference signals. The comparison between both controllers considers the undisturbed and the perturbed cases. Numerical simulations and experimental results demonstrate that the proposed VG-SMC controller provides better overall closed-loop results than those obtained by a fixed-gain sliding mode controller, despite the presence of disturbances.

Identifying promoter sequence architectures via a chunking-based algorithm using non-negative matrix factorisation.

Core promoters are stretches of DNA at the beginning of genes that contain information that facilitates the binding of transcription initiation complexes. Different functional subsets of genes have core promoters with distinct architectures and characteristic motifs. Some of these motifs inform the selection of transcription start sites (TSS). By discovering motifs with fixed distances from known TSS positions, we could in principle classify promoters into different functional groups. Due to the variability and overlap of architectures, promoter classification is a difficult task that requires new approaches. In this study, we present a new method based on non-negative matrix factorisation (NMF) and the associated software called seqArchR that clusters promoter sequences based on their motifs at near-fixed distances from a reference point, such as TSS. When combined with experimental data from CAGE, seqArchR can efficiently identify TSS-directing motifs, including known ones like TATA, DPE, and nucleosome positioning signal, as well as novel lineage-specific motifs and the function of genes associated with them. By using seqArchR on developmental time courses, we reveal how relative use of promoter architectures changes over time with stage-specific expression. seqArchR is a powerful tool for initial genome-wide classification and functional characterisation of promoters. Its use cases are more general: it can also be used to discover any motifs at near-fixed distances from a reference point, even if they are present in only a small subset of sequences.

PWM Controlled Servomechanism

Precise control of aircraft flight control surfaces by the pilot is critical to flight safety. The joystick and control surface positions must be detected accurately and quickly, and the motion mechanism must be operated in such a way as to ensure synchronization between them. The analogue voltage value taken from the potentiometer, which is used as a position sensor in many small aircraft, can be used directly or by converting to digital. 
 In this applied study, the analogue position knowledge received from the potentiometer on the joystick was converted into a PWM signal with an oscillator circuit. The PWM position signal applied to the IR (InfraRed) LED in the transmitter unit is sent as infrared light. The PWM position knowledge detected by the photodiode in the receiver unit was passed through the LPF (Low Pass Filter) and the voltage value of the joystick potentiometer was obtained again. With the mechanism controlled according to the difference between the potentiometer values of the joystick and the control surface, the synchronization between the joystick and the control surface is ensured. In this study, a wireless and stable servomechanism connection is obtained by transmitting PWM position knowledge as IR.

Trajectory tracking control of nonholonomic wheeled mobile robots using only measurements for position and velocity

This paper studies the trajectory tracking control of nonholonomic wheeled mobile robots, and only measurements for Cartesian position and velocity are used. A full-order observer is proposed to estimate the unmeasurable attitude and filter the position signal. Its effectiveness relies on the persistent excitation (PE) condition of non-zero linear velocity. Using the observer states, we design a local tracking controller that guarantees: (a) the linear velocity input is positive, and (b) the position tracking error is convergent to zero locally asymptotically. Experiments performed on a robot built in-house illustrate the control algorithm.

Limitation of Position Signal in Output Feedback Control based on Adaptive Neural Networks of Euler Lagrange Systems

Bu çalışmada, dinamik belirsizliklere sahip Euler Lagrange (EL) sistemlerinin konum takip problemine odaklanılmıştır. Özellikle, konum bilgisi elde edilirken hız bilgisinin kullanıl(a)madığı durum incelenmiştir. İkincil bir amaç olarak, her girişin takip hatasının önceden sınırlandırılması hedeflenmiştir. Konum takip hatasının önceden belirlenen bir bölgede olacak şekilde başlatılıp bu bölgede kalacağı kısıtları altında hedeflenen konumun takip edilmesi motivasyonu ile bir denetleyici tasarlanmıştır. EL sistemlerinin modelindeki belirsizliklerin bir kısmı gürbüz bileşenlerle bastırılarak telafi edilmiş, bir kısmı ise yenilikçi güncelleme kuralları kullanılarak yapay sinir ağları yaklaşımıyla kestirilip denetim yapısında kullanılmıştır. Hız ölçümlerinin mevcut olmaması durumunu telafi etmek için filtre temelli yöntemler kullanılmıştır. Konum sinyalinin sınırlı olması koşulu altında uyarlamalı sinir ağları tabanlı çıkış geri beslemeli yenilikçi bir denetleyici tasarlanmış, kapalı çevrim denetim sisteminin kararlılığı Lyapunov tabanlı metotlarla analiz edilmiştir. Tasarlanan denetleyicinin performansının değerlendirilmesi için iki serbestlik derecesine sahip düzlemsel robot modeli kullanılarak karşılaştırmalı benzetim çalışmaları gerçekleştirilmiştir.

Biometric Recognition Based on Recurrence Plot and InceptionV3 Model Using Eye Movements.

The ability to use eye movement signals as a feature in biometric recognition is a novel characteristic of biometric recognition technology. However, present technologies have not fully exploited the correlation features between eye movement signals. To address this, we propose an eye movement biometric recognition model that is based on recurrence plot encoding and the InceptionV3 model. We first encode the original eye movement signal using the recurrence plot to obtain a two-dimensional image that is then used as input for the InceptionV3 model to perform biometric recognition. Our experimental results using the GazeBaseV2.0 eye movement dataset demonstrate that our proposed model achieved a high biometric recognition accuracy of 96.58% ± 0.66% using the recurrence plot transformation of the horizontal gaze position signals and the InceptionV3 model, surpassing the accuracy achieved by other models. The use of horizontal gaze position eye movement signals for biometric recognition outperforms the use of vertical gaze position signals when using our proposed methods. Furthermore, the biometric recognition that is achieved through recurrent plot encoding is superior to that achieved using Markov transition fields and Gramian angular field transformations.

Measuring Received Signal Strength of UWB Chaotic Radio Pulses for Ranging and Positioning

The use of ultra-wideband (UWB) signals for local positioning is very attractive for practice, because such signals have the potential to provide centimeter precision. In this paper, we consider wireless ranging (distance measurement) and positioning, using one of the kinds of UWB signals, i.e., chaotic radio pulses, which are noise-like signals with no constant shape. The distance measurement is based on an assessment in the receiver of the power of UWB chaotic radio pulses emitted by the transmitter. A new method for estimating their power and its experimental implementation is proposed and described. Experimental layouts of the transmitter and receiver and the principles of their operation are described. To determine the main features of this method under real signal propagation conditions, full-scale indoor measurements were carried out, and statistical estimates of the accuracy were made. We present the results of experimental testing of the proposed approach for positioning the emitter relative to a system of anchors in an office space 6 × 6.5 m2 in the mode of measuring object coordinates on a line and on a plane. The mean absolute error (MAE) of distance measurement (1D) was 25 cm, and the root mean squared error (RMSE) was 39 cm. When positioning on a plane (2D), the MAE of coordinate estimation was 34 cm and the RMSE was 42 cm. The proposed distance measurement method is intended for use in wireless UWB transceivers used in wireless sensor networks.

Control design, analysis, and optimization of fractional-order delayed resonator for complete vibration absorption

The active vibration absorber can eliminate the vibration energy entirely from a primary system through its anti-resonance effect, which is widely applied to vibration-sensitive scenarios. This article focuses on the control design, analysis, and optimization problems for a novel vibration-absorption technique named fractional-order delayed resonator. Specifically, we develop a parameterized form for such a fractional delayed control logic and provide a detailed analysis concerning the control parameters. By the frequency-domain integer-order approximations, we design a control framework that applies to any of the position, velocity, and acceleration signal sources. Then, the particle swarm optimization algorithm is utilized to minimize the transmissibility error at the excitation frequency and determine the optimal approximation frequency band. Additionally, we discuss the stability preservation concern brought by different approximation configurations. Finally, we treat the order of the fraction as an additional tunable parameter to enhance the frequency sensitivity under delay discretization. The overall concept and analysis are validated by numerical simulations.

A Novel Technique to Correct the Unwanted Zero Position Signal of Faulty Encoder for Accurate Speed and Position Estimation of PMSM Drive

A Novel Technique to Correct the Unwanted Zero Position Signal of Faulty Encoder for Accurate Speed and Position Estimation of PMSM Drive

Output feedback control for overhead cranes subject to double-pendulum swing effects and uncertain disturbances

In this paper, a disturbance-observer–based control approach is developed for overhead crane systems. Different from existing control strategies, the issues consisting of the output feedback, input saturation, double-pendulum dynamics, and uncertain disturbances are taken into consideration here. In particular, a disturbance observer is designed first, which can exactly estimate uncertain disturbances. Next, to enhance the performance of the controller, a virtual position signal is constructed and a corresponding Lyapunov function is introduced. Then, based on the provided Lyapunov function and the designed disturbance observer, a composite control approach is developed for overhead crane systems with double-pendulum dynamics and the convergence of the system states is proved via rigorous theoretical analysis. Finally, the effectiveness and robustness of the proposed control approach are verified by simulation tests.

Design of Acoustic Signal for Positioning of Smart Devices.

This paper addresses the limitations of using smartphones in innovative localization systems based on audio signal processing, particularly in the frequency range of 18-22 kHz, due to the lack of technical specifications and noise characterization. We present a comprehensive study on signal design and performance analysis for acoustic communication in air ducts, focusing on signal propagation in indoor environments considering room acoustics and signal behavior. The research aims to determine optimal parameters, including the frequency band, signal types, signal length, pause duration, and sampling frequency, for the efficient transmission and reception of acoustic signals for commercial off-the-shelf (COST) devices. Factors like inter-symbol interference (ISI) and multiple access interference (MAI) that affect signal detection accuracy are considered. The measurements help define the frequency spectrum for common devices like smartphones, speakers, and sound cards. We propose a custom signal with specific properties and reasons for their selection, setting the signal length at 50 ms and a pause time of 5 ms to minimize overlap and interference between consecutive signals. The sampling rate is fixed at 48 kHz to maintain the required resolution for distinguishing individual signals in correlation-based signal processing.

Improved deep learning based multi‐index comprehensive evaluation system for the research on accuracy and real‐time performance of coal gangue particles recognition

AbstractThe problems of insufficient recognition accuracy, poor real‐time performance and lack of consideration of actual working conditions in the process of intelligent construction of coal mines make this technology still in the research stage and not applied in practical engineering. The purpose of this paper is to establish an accurate and real‐time recognition model, which can quickly distinguish the vibration acceleration signals of coal and gangue under the influence of external factors such as impact position, velocity, and direction by using the different physical properties of coal and gangue particles. Therefore, the accuracy and real‐time of coal gangue recognition model established by different convolutional neural networks (CNN) structures and different position signal input are studied. First, to meet the real‐time requirements, an original CNN recognition model composed of single convolution layer and single pooling layer is established, and the data collected by seven sensors are input in the form of two‐dimensional matrix. However, the stability of the training and test results is insufficient. To solve this problem, once improved CNN (OI‐CNN) recognition model with multiconvolution layers and multipooling layers is built by deepening the network. The experimental results show that the stability and accuracy are improved, but the real‐time performance is poor. Furthermore, through parameter adjustment, the OI‐CNN is changed to the twice improved CNN (TI‐CNN), and the sensor data at different positions are input in the form of one‐dimensional vectors. The results show that the accuracy and real‐time performance of the TI‐CNN coal gangue recognition model are further improved. Finally, according to the research purpose of this paper, the weights of CNN indexes are given, and a multi‐index comprehensive evaluation system (MICES) is established. With the original CNN recognition model as the control, the OI‐CNN recognition model and the TI‐CNN recognition model at different positions are quantitatively compared to obtain the comprehensive evaluation scores of each model. The results show that the MICES of the coal gangue recognition model established based on the TI‐CNN structure and the data input of a single position sensor is the highest, while the sensor position has little effect on the recognition results.

Current Fault Tolerance Control Strategy for 3-Phase Switched Reluctance Motor Combined With Position Signal Reconstruction

In this paper, a fault-tolerant control method for switched reluctance motors is proposed for the faults of power converters that occur during the operation of switched reluctance motors. The method combines position reconstruction strategies based on fault tolerant control. The fault detection scheme can accurately determine the faults component and faults type, and then and then maintain the motor drive through the current reconstruction. The position reconstruction scheme improves the traditional inductance detection method, which can improve the situation that the position signal fault leads to the current reconstruction fault. In addition, this paper sets constraints on the reconstruction of position signals to enhance the stability and robustness of position signals. Finally, the stability of the proposed method is verified by experiments.

MagicInput: Virtual Handwriting Interface Using Ubiquitous WiFi Signals

Past few years have witnessed the great potential of exploiting WiFi signals for positioning. Prior work focus on discovering the absolute locations of a radio source, and have achieved promising accuracies of tens of centimeters. However, many applications such as aerial gesture or handwriting tracking are more concerned with the detailed motion shape of the target rather than its exact locations, which require a several fold higher accuracy. To this end, we present MagicInput, a virtual handwriting interface by tracking the motion traces of a WiFi source. Based on Channel State Information (CSI), MagicInput elaborately devises an incremental motion-based tracking model by correlating the motion traces with the angle and length variations of propagation paths. The model shifts the tracking task from the transceiver view to the antenna array-oriented view, and eliminates the need for prior knowledge of anchor locations. MagicInput proposes an end-to-end pipeline for tracking refinement, by interference suppression, motion segmentation, and an integrated grasp pressure sensorbased motion instance detection. We prototype MagicInput using off-the-shelf WiFi radios, and extensive experiments attest that MagicInput can achieve the accuracy of 8.5 mm confronting diverse users and environment conditions. With ubiquitous WiFi signals, MagicInput can transform any region into an interactive handwriting interface with millimeter accuracy.

The Design of a Reaction Flywheel Speed Control System Based on ADRC

The reaction flywheel is a crucial operational component within a satellite’s attitude control system. Enhancing the performance of the reaction flywheel speed control system holds significant importance for satellite attitude control. In this paper, an active disturbance rejection control (ADRC) approach is introduced to mitigate the impact of uncertain disturbances on reaction flywheel speed control precision. The reaction flywheel speed control system is designed as an ADRC controller due to the current challenge of measuring unknown disturbances accurately in the reaction flywheel system. To derive the rotor’s speed observation value and the estimated total disturbances value, the sampled data of the reaction flywheel rotor position and torque control signal are fed into the extended state observer. The estimated total disturbances value is compensated on feedforward control, which could mitigate significantly the effects of various nonlinear disturbances. The paper initially establishes the rationale behind the reaction flywheel ADRC controller through theoretical analysis, followed by analysis of the differences of performance of reaction flywheel control by the ADRC controller and the PID controller in MATLAB/SIMULINK. Simulation results demonstrate the evident advantages of the ADRC controller over the PID controller in terms of speed command tracking capability and disturbances suppression ability. Subsequently, the ADRC controller program and the PID controller program are implemented on the reaction flywheel control circuit, and experiments are conducted to contrast speed command tracking and disturbance suppression. Importantly, the experimental outcomes align with the simulation results.

From the material behaviour to the thermo-mechanical long-term response of asphalt pavements and the alteration of surface drainage due to rutting: a sensitivity study

ABSTRACT In this contribution, a simulation chain for the thermo-mechanical and hydromechanical analysis (surface drainage) of a pavement structure during its whole service life is applied to a typical asphalt pavement (Bk100) used for motorways in Germany. Transient load signals for each tyre position of a truck-trailer combination (vehicle) are generated from a multibody analysis of the vehicle driving on a motorway with rough pavement surface. Material model parameters are derived from experimental identification tests of asphalt materials. The model parameters are used together with a continuum-mechanical description of the asphalt material representing the thermo-mechanical material behaviour at the material scale. The material response of the pavement layers is integrated on the structural scale by using the finite element method (FEM) in combination with an arbitrary Lagrangian-Eulerian (ALE) formulation and equivalent tyre loads of a representative, finite element (FE) discretised truck tyre rolling on an FE discretised pavement section. Different scenarios of rut formation are computed by varying different influence factors (climate temperature, vertical tyre force, type of asphalt material of the surface layers etc.). During the subsequent hydromechanical analysis of the pavement, the simulated deformed geometry of the pavement surface is used to numerically compute surface drainage characteristics.

Ambiguity and vagueness in party competition

A central theme emerging from recent research on party competition is that political actors sometimes remain deliberately opaque in their communication. This phenomenon has been investigated under labels such as position-blurring, ambiguity, issue clarity or ideological clarity. In this paper we propose a distinction between two concepts that are sometimes conflated in this literature: ambiguity and vagueness. While ambiguity means that there is substantial variance in parties' positional signals, vagueness denotes political statements that are non-committal in terms of the policy action to be taken or the outcome to be achieved. We explore the co-variation of these two dimensions and their relationship to issue ownership and government status using manifesto data produced by the Austrian National Election Study. These data are unique in that they provide detailed positional information as well as information on policy commitment (election pledges). We show that the two dimensions are uncorrelated and have opposite relationships with issue ownership (vagueness positive, ambiguity negative). We conclude that analyses of position-blurring in party competition should take different strategies of non-clarity in party communication into account.

Mixed tiny path smoothing method based on sliding convolution windows for CNC machining

The machining toolpaths of complex free-form surface parts are generated using computer-aided manufacturing (CAM) systems and programmed by a series of mixed tiny paths composed of tiny lines, arcs, and non-uniform rational B-spline (NURBS). The mixed tiny paths need to be smoothed to eliminate the tangential discontinuities at corners. This paper proposes a mixed tiny path smoothing method based on sliding convolution windows (MSSCW). In this method, the mixed tiny path is firstly converted into a positional signal along the travel length in the spatial domain, and then sliding convolution windows, which centered on each original interpolation point, are used to generate high-order continuous smoothed toolpath. Finally, the smoothing error is checked and corrected by modifying the length duration of the sliding convolution windows. Compared with conventional path smoothing method, the MSSCW method is suitable for various computer numerical control (CNC) machining toolpaths, and the continuity of the smoothed toolpath can be adjusted according to user requirements. Consequently, the feasibility and effectiveness of the proposed method are validated in simulations and experimental results which realize the improvement of the machining quality of complex free-form surfaces.

5-axes Levitation of a Rotor by Active Magnetic Bearings Employing Direct Output Feedback Control

In recent years the application of active magnetic bearings (AMB), as supporting element as well as vibration controller for rotors, has attracted considerable attention from researchers. In this work an attempt has been made for the complete levitation of a rotor weighing 4 kg, supported on two radial active magnetic bearings and two axial passive magnetic bearings (PMB) resulting in 5-axes levitation. The active bearings working in the mode of attraction make the system inherently unstable. Herein, a direct output feedback control scheme based on proportional and derivative of position signal has been employed to achieve stability. The active magnetic bearings consist of electromagnetic actuators, proximity probes for position measurement, feedback controller and current feedback type power amplifier. The passive bearings consisting of axially magnetized circular permanent magnets work in the mode of repulsion. The design of the electromagnetic actuator has been carried out considering load carrying capacity of the AMB, core loss and the resistive loss in the coil, so that the temperature rise in the core as well as in the coil is within allowable limit. Design of the feedback controller is based on direct output feedback control scheme, which makes the controller design easier and implementation of the controller hardware becomes simpler. The feedback controller parameters have been selected appropriately to generate required stiffness and damping in the AMBs for stable levitation of the rotor. The rotor has been driven up to a speed of 2000 rpm.