Adaptive Time Delay Estimation Research Articles

Improved variable step adaptive filtering algorithm and its application in time delay estimation for continuous wave dual-sensor pulse signals

Continuous wave mud pulse transmission is crucial for wireless logging, but surface pump noise disrupts upstream mud pulses, hindering downhole information extraction. At a theoretical level, the dual-sensor differential denoising approach is an excellent technology for suppressing pump noise, but precisely identifying the time delay, which has a considerable impact on the denoising effect, remains a challenge. This paper provides an improved variable step-size adaptive time delay estimation method TVSS-LMSTDE to address this issue. Iteration time regulates the change in step size. The preset adjustment principle states that modifying parameters ζ and γ controls the learning features of step size. A series of stable and erratic dual-sensor continuous wave mud pulse signals interfered by various noise intensities are created in the simulation, and the performance of three different variable step-size technologies—error-oriented, nonlinear relationship, and iterative time regulation—in terms of convergence speed, estimation stability, and calculation amount are compared and analyzed. The results show that the iterative time regulation technique produces a minimal mean square error in time delay estimate, with generally steady estimation and excellent accuracy. When applied to hydraulic cycle tests, the technique accurately gets the time delay value of dual-sensor signals, giving critical support for the successful recovery of mud pulse data severely disrupted by pump noise.

Adaptive Time Delay Estimation Based on Signal Preprocessing and Fourth-Order Cumulant

Adaptive Time Delay Estimation Based on Signal Preprocessing and Fourth-Order Cumulant

Adaptive time-delay estimation and control of optimized Stewart robot

Aiming at a more efficient and accurate performance of parallel manipulators in the existence of complex kinematics and dynamics, a robust generalizable methodology is proposed here for an integrated 6-DOF Stewart platform with rotary time-delayed actuators torque control. The suggested method employs a time-delay linear–quadratic integral regulator with online artificial neural network gain adjustment. The unknown time-delay is estimated through a novel robust adaptive estimator. The global asymptotic stability of the estimator is proved via a Lyapunov function. The controller is developed in MATLAB software and implemented on the robot designed in ADAMS software to ensure that the real-time tracking error of a nonlinear system with an unknown time-delay is kept to a minimum. The sensitivity of the controller to the parameter choices is studied via implementing the controller in ADAMS software and is validated by investigating the performance on a naturalistic fabricated robot. The approach is assessed using simulation and experimental tests to show the feasibility, optimum, and zero-error convergence of the technique developed.

Leak location study of water pipeline based on CEEMDAN-CC at low SNR

Leak location studies of water supply pipes are crucial to reducing water waste and eliminating potential hazards. However, for the situation where the noise intensity is much greater than the leak signal intensity, the traditional noise-reduction localization methods have become ineffective. Therefore, an adaptive time-delay estimation method based on complete ensemble empirical mode decomposition with adaptive noise and cross-correlation (CEENDAN-CC) is proposed, which can automatically extract the feeble leakage signal from the strong noise. In this paper, the principle and steps of the method are introduced in detail, and the validity and superiority of the method are verified from signal simulations. The results show that after processing, the signal-to-noise ratio (SNG) of the signal is substantially enhanced, the peak of the correlation function is obvious, and the accuracy of the time-delay estimation is significantly enhanced. Compared with other algorithms, the method found more accurate time-delay and had better noise immunity.

Leakage Detection and Localization of Water Pipeline Using Multi-features and Adaptive Time Delay Estimation

The leakage of water in pipelines severely affects the environment and economy. However, there are limitations in the effectiveness of existing leak detection and localization techniques and methodologies. In this paper, we propose a novel leakage detection and localization method based on the multiple time-frequency features, a neural network, and an adaptive time delay estimation algorithm. First, we use spectral subtraction and wavelet denoising to reduce the effects of noise. In addition, to ensure and improve the accuracy of leakage detection in complex realistic environments, we propose the use of multi time-frequency features that can comprehensively represent the leak signal and make the neural network more robust to train a radial basis function (RBF)neural network to detect the leak signal. Further, we extract multiple features of the leakage signal and input into the RBF neural network to train. Moreover, to prevent the impulsive components of environmental noise and improve localization accuracy, we further propose the use of a fractional lower-order statistics (FLOS) based adaptive time delay estimation algorithm to estimate the time delay and locate the leakage. The simulation results show that the detection and localization performance of the proposed method is superior to those of existing schemes.

Adaptive neural network control for flexible telerobotic systems with communication constraints

This paper investigates the synchronous control problem for a class of flexible telerobotic systems subject to system uncertainties and communication constraints. In view of the asymmetric time-varying communication delays, an adaptive time-delay estimator is designed to reduce the impacts of delays on the system. Moreover, by combining the neural networks and parameter adaptive method, the uncertainties of system dynamics are estimated and compensated. Based on these efforts, a new adaptive compensation control protocol is proposed. Additionally, input quantization in network control induced chattering phenomenon and unknown parameters is also dealt with by the adaptive compensation method. A useful characteristic of this paper is that the “complexity explosion” problem caused by the backstepping technique is circumvented effectively. Finally, sufficient conditions are derived for the synchronous control of the master-slave flexible telerobotic system under Lyapunov stability theory. A numerical example of flexible-joint robotic system is provided to illustrate the effectiveness of the proposed control schemes.

Time delay estimation-based reactionless augmented adaptive sliding mode control of a space manipulator’s pregrasping a target

AbstractReaction null space (RNS) planning and control of a planar three-link space manipulator’s pregrasping a spinning target are studied. First, the Lagrange dynamic model of the manipulator was established. Second, the RNS motion planning algorithm was derived, and the vector norm constraint algorithm of RNS planning was addressed to ensure certain joint angular acceleration constraints were satisfied. Furthermore, an augmented adaptive sliding mode controller based on time delay estimation (TDE) was proposed. This controller estimated the unknowns of the system by TDE technology, in which accurate and complete dynamics were not required, and an adaptive TDE was introduced to decrease the estimation errors and avoid serious chattering. Finally, numerical simulations were carried out to verify the effectiveness of the proposed RNS planning and control algorithm.

Multi Observer-Based Sliding Mode Load Frequency Control With Input Delay Estimation

Abstract The letter proposes frequency stability in power systems with input delay. A closed loop system can be oscillatory or even unstable without the exact knowledge of delay. Therefore, it is desirable to design a control scheme which is based on the estimation of unknown delay. The proposed design consists of an infinite dimensional observer with an adaptive time delay estimation and a sliding mode controller (SMC). The merit of the proposed concept lies in the fact that the unknown delay is valued by just estimating the smallest delay segment. The controller input is obtained from a set of sequential observers that predicts the system states and ensures asymptotic stability of the closed loop system with input delay estimation. The existence of sliding mode and the closed loop system stability is proved thanks to the Lyapunov and Lyapunov–Krasovskii candidate functionals, respectively. Simulation results confirm the effectiveness of the proposed design.

Continuous Non-singular Terminal Sliding Mode Control of Space Robot Based on Adaptive Time Delay Estimation

Continuous Non-singular Terminal Sliding Mode Control of Space Robot Based on Adaptive Time Delay Estimation

Generalized Weighted Adaptive Time Delay Estimation Algorithm Based on Minimum Average P Norm

The time delay estimation algorithm is one of the important factors of sound source localization. The generalized weighted adaptive time delay estimation algorithm is limited by the environmental conditions of signal and noise, and has great limitations in non-Gaussian environments. In order to make the algorithm suitable for non-Gaussian environments, and to retain the advantages of the algorithm in effectively suppressing harmonics, this paper combines the minimum average P norm (LMP) with the generalized weighting function, and proposes a method based on the minimum average P norm. The generalized weighted adaptive time delay estimation algorithm of the number can make the algorithm suitable for non-Gaussian environments, and for the shortcomings of slow iteration speed and large calculation amount for the minimum average P norm, the Sigmoid function is introduced to further improve the parameter selection in the algorithm. MATLAB simulation experiments show that the algorithm in this paper can effectively suppress the existence of harmonics in a non-Gaussian environment, and has strong convergence, high accuracy of time delay estimation, and fast iteration speed. It can be based on time delay estimation in a non-Gaussian environment. The positioning plays a certain role.

Distributed recursive filtering for multi-sensor networked systems with multi-step sensor delays, missing measurements and correlated noise

This paper is concerned with the distributed recursive filtering for the discrete-time nonlinear multi-sensor networked system with multi-step sensor delays, missing measurements and correlated noise. Based on the innovation statistical distance, an adaptive time delay estimation method, which belongs to the online methods, is derived to determine whether the measurement is acquired or not along with the time delay step. Then, a nonlinear system model is founded based on a set of selected Bernoulli distributed random variables to describe the multi-step sensor delays, missing measurements and correlated noise. The obtained time delay step can be used to update parameters of the proposed measurement model. Next, a distributed recursive filtering is designed based on linear fitting (LF) and weighted average consensus (WAC) to solve the nonlinear state estimation in the multi-sensor networked system. Meanwhile, a selection strategy is designed based on the innovation statistical distance for the weighted factors to improve the distributed fusion accuracy. Further, filtering errors of the distributed recursive filtering are proved to be exponentially bounded in mean square. Numerical simulations are conducted to evaluate the performance of the proposed algorithm.

Adaptive time delay control for cable-driven manipulators using fuzzy logic algorithm

A new adaptive time delay estimation technique with sliding mode control method is proposed and investigated in this passage for cable-driven manipulators. Time delay estimation technique is an effective tool to compensate for unmodeled dynamics and unknown disturbance, and adaptive time delay estimation performs better due to its adaptive control gain. The proposed adaptive method is based on the fuzzy logic algorithm which has a great advantage in input–output mapping thank to its flexibility. Tuning procedure is addressed to reveal the implementation of the newly proposed algorithm. Moreover, the desired trajectory is taken as an input of adaptive algorithm and better control performance is obtained through this attempt. The proposed controller is ultimately uniformly bounded and proof using the Lyapunov method is provided. Finally, comparative experiments show the validity and effectiveness of the proposed controller.

An Adaptive Time Delay Estimation Method for Broadcast Audio Based on Power Cepstrum

Abstract This paper proposes an adaptive time delay estimation method for broadcast audio based on power cepstrum. First, it adds two real-time broadcast audio signals with the same content but with a time delay to obtain a mixed signal, then segment the mixed signal, and obtain a power cepstrum for each mixed signal. Afterwards, the time delay of the two audio signals is determined by using the feature that the power cepstrum of the mixed signal can peak at the time delay. The experimental results show that this method can obtain more accurate time delay results. And it has higher robustness and faster than traditional methods such as generalized cross-correlation time delay estimation algorithm.

A direct robust nonsingular terminal sliding mode controller based on an adaptive time-delay estimator for servomotor rigid robots

ABSTRACT In this paper, a novel adaptive robust controller is presented for high-accuracy tracking control of servomotor rigid robotic systems based on a modified nonsingular terminal sliding scheme incorporated with an adaptive time-delay estimation (TDE) technique. To effectively estimate unknown systematic dynamics, the model-free estimation is designed with a basic TDE and a new self-learning mechanism, which is able to automatically find the proper nominal input gains for the best TDE error. The control objective is then realized by a control process which consists of a model-compensation phase, highly robust control term and reaching-guarantee law. The compensator uses the TDE terms obtained to eliminate the dynamic effect. For providing the flexible robustness to the control system, the robust gain is actively adjusted based on information of the estimation system. The reaching-control rule employs nonlinear folding functions to promptly drive a synthesized sliding manifold back to zero. Finite-time stabilities of both the adaptive TDE and the closed loop system are proven using Lyapunov-based constraints extended from new folding-convergence analyses. The effectiveness and feasibility of the closed loop system are confirmed throughout intensive real-time experiments under various testing conditions.

Adaptive time delay estimation based on the maximum correntropy criterion

In this paper, a novel adaptive time delay estimation (TDE) method under the existence of amplitude attenuation is proposed for the impulsive noise environment. We present a closed form of the recursive solution for the TDE by using the maximum correntropy criterion (MCC). First, a two-step TDE method, which has the advantage of simplicity, is proposed. In this approach, the coefficients in the noncausal finite impulse response (FIR) filter are employed to model the time delay. Furthermore, to improve the robustness of the proposed two-step algorithm, a closed form of the recursive solution for the direct TDE is proposed, which does not have any free parameter, as in the two-step algorithm in gradient-based techniques. Finally, the convergence property regarding the direct TDE algorithm is performed.

Adaptive Multi-Observer Design for Systems with Unknown Long Input Delay

This paper deals with the problem of stabilization of systems with a constant delay in the actuator. The time-delay is unknown and can be considerably long, involving an interesting challenge from the control point of view. The proposed control scheme is based on a set of infinite dimensional observers with an adaptive time-delay estimation. The convergence of the observers is studied considering the time-varying delays introduced by the delay estimation. A stability analysis of the closed-loop control system is provided. The proposed observer-based controller is tested by means of numerical simulation, considering an unstable plant.

An Ultra-Low-Power Polarity-Coincidence Feedback Time-Delay-to-Digital Converter for Sound-Source Localization

The time-delay between audio signals in a microphone array is the most important feature for sound-source localization. This article presents a polarity-coincidence, adaptive time-delay estimation (PCC-ATDE), a mixed-signal technique that uses 1-bit quantized signals and a negative-feedback architecture to directly determine the time-delay between signals in the analog inputs and convert it to a digital number. This direct conversion, without a multi-bit analog-to-digital converter and further digital-signal processing, allows for ultra-low power consumption. A prototype chip in 0.18- $\mu {\mathrm{ m}}$ CMOS with four analog inputs consumes 78 nW with a three-channel 8-bit digital time-delay output while sampling at 50 kS/s with a 20-us resolution and 6.06 ENOB. We present a theoretical analysis for the non-linear, signal-dependent feedback loop of the PCC-ATDE. A delay-domain model of the system is developed to estimate the power-bandwidth of the converter and predict its dynamic response. Results are validated with experiments using real-life stimuli, captured with a microphone array, that demonstrates the ability of the technique to localize a sound source. The chip is further integrated into an embedded platform and deployed as an audio-based vehicle-bearing IoT system.

FPGA implementation of adaptive time delay estimation for real‐time near‐field electromagnetic ranging

SummaryThe near‐field electromagnetic ranging systems exploit the near‐field phase behavior of low frequency signals for indoor real‐time ranging. Conventionally, phase detector is used to determine the phase of electric and magnetic fields. Subsequently, the phase difference is used to estimate a distance value. In adaptive time delay estimation approach, the time delay between electric and magnetic signals is used instead of phase difference for an estimation. This method does not require a priori knowledge of the transmitting signals and can obtain better performance in low signal‐to‐noise ratio environment. In this paper, we propose a digital near‐field electromagnetic ranging system design and implement it on field‐programmable gate array. This system is composed of time delay estimator, frequency estimator, and received signal strength indicator. A maximum correntropy criterion–based explicit time delay estimation algorithm with a delay in the coefficient update is implemented to estimate the time delay in real time. The fast Fourier transform and received signal strength indicator modules determine the signal frequency and the signal strength received, respectively. Our experimental results indicate that the delayed maximum correntropy criterion–based explicit time delay estimation algorithm has fast convergence rate and good steady‐state performance in an impulsive noise environment.

Highly accurate adaptive TOF determination method for ultrasonic thickness measurement

Determining the time of flight (TOF) is very critical for precise ultrasonic thickness measurement. However, the relatively low signal-to-noise ratio (SNR) of the received signals would induce significant TOF determination errors. In this paper, an adaptive time delay estimation method has been developed to improve the TOF determination’s accuracy. An improved variable step size adaptive algorithm with comprehensive step size control function is proposed. Meanwhile, a cubic spline fitting approach is also employed to alleviate the restriction of finite sampling interval. Simulation experiments under different SNR conditions were conducted for performance analysis. Simulation results manifested the performance advantage of proposed TOF determination method over existing TOF determination methods. When comparing with the conventional fixed step size, and Kwong and Aboulnasr algorithms, the steady state mean square deviation of the proposed algorithm was generally lower, which makes the proposed algorithm more suitable for TOF determination. Further, ultrasonic thickness measurement experiments were performed on aluminum alloy plates with various thicknesses. They indicated that the proposed TOF determination method was more robust even under low SNR conditions, and the ultrasonic thickness measurement accuracy could be significantly improved.

A Robust and Higher Precision Time Delay Estimation Method Facing Low Signal to Noise Ratio Conditions

Many available signals in the real world are usually weak with impulse noises and/or outliers, and we also need to have higher estimation precision in applications. Our focus of attention is pretty much on integrating robustness and accuracy under lower signal to noise ratio (SNR) with impulse noises. Although traditional fractional adaptive time delay estimation (TDE) methods have higher precision, the results of estimation are unreasonable when the signals contain some impulse noises. While, most proposed robust algorithms later can work well mainly with high SNR. In this paper, considering the practical problem in equipment fault acoustic localization based on TDE methods, an improved robust fractional adaptive time delay estimation method is addressed facing lower SNR conditions. First, the impulse noises are modeled as Alpha stable distribution, and the integer part of TDE is getting by using covariate correlation approach. Then, the integer estimation value is used as initial parameter value of time delay. Covariant sequence is the input of time delay estimator. Next, fractional TDE value is adaptive obtained by iteration under minimum average <i>p</i> norm criterion. Covariant sequence weakens irrelevant noises, meanwhile preserves time delay information between original sequences. Computer simulations and comparative experiments show that improved method has better estimation results. This method is robust and higher precision, and especially under impulse environment and low SNR conditions.