Time-delay Estimation Technique Research Articles

A high-order time-delay difference estimation method for signal enhancement in the distorted towed hydrophone array.

In passive sonar systems, deviations from an ideal linear configuration can significantly impair the beamforming performance of towed hydrophone arrays. This paper presents a method aimed at improving the underwater acoustic signals in the presence of array distortion. The method is centered on a high-order time-delay difference estimation technique utilizing time-frequency autofocus. Initially, a detailed signal model is established that captures the distinctive characteristics of distorted arrays. Subsequently, an algorithm is introduced for high-order time-delay difference estimation to enhance signal fidelity by leveraging phase information within narrowband components originating from incidental acoustic sources. Additionally, a quality metric to evaluate these components is introduced, facilitating the practical implementation of the method. The effectiveness of the proposed approach is validated through both simulation and experimental results, demonstrating its superiority over existing techniques. Importantly, this method does not require prior knowledge of the distortion pattern, making it adaptable to various non-linear array configurations.

Model-free composite sliding mode adaptive control for 4-DOF tower crane

For the 4-DOF tower crane system, the lack of actuated number brings great challenges to the realization of accurate positioning and effective swing suppression, particularly with system uncertainties and disturbances. To address this, a model-free composite sliding mode (CSM) adaptive control method for 4-DOF tower crane system with multiple types of uncertainties is proposed. Specifically, the CSM surfaces are constructed by coupling the driving and non-driving variables to enhance the ability to suppress swing. Based on CSM surfaces, not only the asymptotic stability of the system equilibrium point is proved, but also the continuity of the designed control law is ensured. In addition, according to time delay estimation (TDE) technique, system uncertainties and disturbances are dealt with, and achieving model-free control. Finally, the controller is implemented on a 4-DOF tower crane experiment platform, and the effectiveness of the proposed control strategy is verified by four sets of hardware experiments.

Adaptive Backstepping Time Delay Control for Precision Positioning Stage with Unknown Hysteresis

Piezoelectric-actuated precision positioning stages are widely used in high-precision instruments and high-end equipment due to their advantages of high resolution, fast response, and compact size. However, due to the strong nonlinearity of hysteresis, the presence of hysteresis in piezoelectric actuators seriously affects the positioning accuracy of the system. In addition, it is challenging to identify the model parameters for hysteresis. In this paper, an adaptive backstepping time delay control method is proposed for piezoelectric devices system with unknown hysteresis. Firstly, the Bouc–Wen model is used to describe the hysteresis characteristics, and the model is interpreted as a linear term and a bounded uncertain hysteresis term. Then, the time delay estimation technique is used to estimate the hysteresis term of the Bouc–Wen model online, and the unknown parameters of the system and hysteresis model are obtained through adaptive updating laws. Furthermore, the stability of the control scheme is proved based on Lyapunov stability theory. Finally, the effectiveness and superiority of the proposed control scheme are demonstrated by comparing it with two typical hysteresis compensation control algorithms through three different sets of input signals.

A model free adaptive‐robust design for control of robot manipulators: Time delay estimation approach

SummaryThis paper addresses a new robust control scheme for tracking control of the robot manipulators. This algorithm employs time delay estimation (TDE) technique in combination with backstepping control strategy. The suggested control scheme has no dependency on the robot dynamic model and knowing the bound of the inertia matrix is enough to develop this controller. To develop the idea, at first the boundedness of the TDE errors is analyzed by Lyapunov‐Krasovskii approach. Next, the proposed TDE based adaptive backstepping nonsingular terminal sliding mode control (ABNTSMC) algorithm is developed. In this way, a novel adaptive‐robust term is employed to defeat the chattering phenomenon. Moreover, the closed‐loop stability of the system is proven through Lyapunov second approach. Fast transient response, supreme robustness, and chattering‐free as the premier specifications are gained employing the proposed control algorithm. The efficiency of the suggested control scheme is illustrated through some simulations on an industrial robot and the results are compared with some other control algorithms. Finally, the practical effectiveness of the proposed TDE based control algorithm is verified through some experiments on a parallelogram robot manipulator.

An improved TDE technique for derivation of 2D turbulence structures based on GPI data in toroidal plasma

This paper reports an improved time-delay estimation (TDE) technique for the derivation of turbulence structures based on gas-puff imaging data. The improved TDE technique, integrating an inverse timing search and hierarchical strategy, offers superior accuracy in calculating turbulent velocity field maps and analyzing blob dynamics, which has the power to obtain the radial profiles of equilibrium poloidal velocity, blob size and its radial velocity, even the fluctuation analysis, such as geodesic acoustic modes and quasi-coherent mode, etc. This improved technique could provide important 2D information for the study of edge turbulence and blob dynamics, advancing the understanding of edge turbulence physics in fusion plasmas.

Finite-Time Robust Flight Control of Logistic Unmanned Aerial Vehicles Using a Time-Delay Estimation Technique

This paper proposes a cascaded dual closed-loop control strategy that incorporates time delay estimation and sliding mode control (SMC) to address the issue of uncertain disturbances in logistic unmanned aerial vehicles (UAVs) caused by ground effects, crosswind disturbances, and payloads. The control strategy comprises a position loop and an attitude loop. The position loop, which functions as the outer loop, employs a proportional–integral–derivative (PID) sliding mode surface to eliminate steady-state error through an integral component. Conversely, the attitude loop, serving as the inner loop, utilizes a fast nonsingular terminal sliding mode approach to achieve finite-time convergence and ensure a quick system response. The time-delay estimation technique is employed for the online estimation and real-time compensation of unknown disturbances, while SMC is used to enhance the robustness of the control system. The combination of time-delay estimation and SMC offers complementary advantages. The stability of the system is proven using Lyapunov theory. Hardware-in-the-loop simulation and flight tests demonstrate that the control law can achieve a smooth and continuous output. The proposed control strategy can be effectively applied in complex scenarios, such as hovering, crash recovery, and high maneuverability flying, with significant practicality in engineering applications.

Alternating direction method of multipliers for displacement estimation in ultrasound strain elastography.

Ultrasound strain imaging, which delineates mechanical properties to detect tissue abnormalities, involves estimating the time delay between two radio-frequency (RF) frames collected before and after tissue deformation. The existing regularized optimization-based time-delay estimation (TDE) techniques suffer from at least one of the following drawbacks: (1) The regularizer is not aligned with the tissue deformation physics due to taking only the first-order displacement derivative into account; (2) The -norm of the displacement derivatives, which oversmooths the estimated time-delay, is utilized as the regularizer; (3) The modulus function defined mathematically should be approximated by a smooth function to facilitate the optimization of -norm. Our purpose is to develop a novel TDE technique that resolves the aforementioned shortcomings of the existing algorithms. Herein, we propose employing the alternating direction method of multipliers (ADMM) for optimizing a novel cost function consisting of -norm data fidelity term and -norm first- and second-order spatial continuity terms. ADMM empowers the proposed algorithm to use different techniques for optimizing different parts of the cost function and obtain high-contrast strain images with smooth backgrounds and sharp boundaries. We name our technique ADMM for totaL variaTion RegUlarIzation in ultrasound STrain imaging (ALTRUIST). ALTRUIST's efficacy is quantified using absolute error (AE), Structural SIMilarity (SSIM), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and strain ratio (SR) with respect to GLUE, OVERWIND, and -SOUL, three recently published energy-based techniques, and UMEN-Net, a state-of-the-art deep learning-based algorithm. Analysis of variance (ANOVA)-led multiple comparison tests and paired -tests at overall significance level were conducted to assess the statistical significance of our findings. The Bonferroni correction was taken into account in all statistical tests. Two simulated layer phantoms, three simulated resolution phantoms, one hard-inclusion simulated phantom, one multi-inclusion simulated phantom, one experimental breast phantom, and three in vivo liver cancer datasets have been used for validation experiments. We have published the ALTRUIST code at http://code.sonography.ai. ALTRUIST substantially outperforms the four state-of-the-art benchmarks in all validation experiments, both qualitatively and quantitatively. ALTRUIST yields up to , , and SNR improvements and , , and CNR improvements over -SOUL, its closest competitor, for simulated, phantom, and in vivo liver cancer datasets, respectively, where the asterisk (*) indicates statistical significance. In addition, ANOVA-led multiple comparison tests and paired -tests indicate that ALTRUIST generally achieves statistically significant improvements over GLUE, UMEN-Net, OVERWIND, and -SOUL in terms of AE, SSIM map, SNR, andCNR. A novel ultrasonic displacement tracking algorithm named ALTRUIST has been developed. The principal novelty of ALTRUIST is incorporating ADMM for optimizing an -norm regularization-based cost function. ALTRUIST exhibits promising performance in simulation, phantom, and in vivoexperiments.

Shifting asymmetric time-varying BLF-based model-free hybrid force/position control for 3-DOF SEA-based manipulator with random initial error

In this work, a shifting asymmetric time-varying barrier Lyapunov function (BLF)-based model-free hybrid force/position controller (SABMHC) is proposed for the endpoint of the 3-DOF series elastic actuator (SEA)-based manipulator which can be used for machining of large curved surfaces. The proposed SABMHC contains a force sub-control loop and a position sub-control loop. The force sub-control loop converts the force control into position control based on the idea of impedance control, and realizes the hybrid force/position control through the position sub-control. Then, in order to achieve accurate trajectory tracking control of the position sub-control loop, a shifting asymmetric time-varying BLF-based model-free controller is proposed, which includes the error shifting function, asymmetric time varying BLF, time-delay estimation (TDE) technique, and adaptive compensation term. To prevent the random initial error from being so large that it exceeds the pre-set boundary and affects the steady-state response, an error shifting function is introduced. The error shifting function can make the shifting error independent of the tracking error before reaching the pre-set shifting time, so as to achieve better control performance by setting a small pre-set boundary for the shifting error. With the Lyapunov function, the designed SABMHC can ensure that the stability and the shifting error converges within the pre-set boundary in a finite time. Finally, the effectiveness and benefits of the proposed SABMHC are analyzed by comparison with the TDE-based intelligent PID (TDE-iPD) and BLF-based sliding-mode controller (BLF-SMC).

Model-free predictive current control of Syn-RM based on time delay estimation approach

Abstract This paper investigates an optimal model-free control design for a synchronous reluctance motor (Syn-RM) with unknown nonlinear dynamic functions, parameter variations, and disturbances. The idea is to combine a predictive control with a time-delay estimation technique (TDE) in order to successfully deal with the system’s uncertainties and make the Syn-RM control scheme easy to implement in real-time. This model-free control strategy comprises two cascade control loops namely outer and inner loops. The outer loop is designed for the mechanical part of Syn-RM to ensure the convergence of the speed dynamics by using a proportional-integral controller while the inner loop is developed to control the uncertain dynamics of currents via an optimal robust controller. In the proposed current loop, the predictive control is enhanced by the inclusion of ultra-local model theory where dynamic functions and disturbances are estimated by instantaneous input-output measurements of the Syn-RM using the TDE approach. Moreover, a particle swarm optimization (PSO) algorithm is also proposed to find the optimal design parameters to improve the dynamic performances of the closed-loop control system. Numerical validation tests of the proposed TDE-based model-free predictive current control (TDE-MFPCC) method are performed in the simulation environment of the Syn-RM system, and the results show the robustness and the effectiveness of the proposed TDE-MFPCC compared to the conventional model-based PCC.

Model‐free prescribed performance fast nonsingular terminal sliding mode control with practical finite‐time stability of uncertain robot manipulators

AbstractThis paper addresses the problem of robust and high precision trajectory tracking control of uncertain robot manipulators with prescribed performance. Time delay estimation (TDE) technique is employed to estimate system model, then a new self‐adjusting strategy (SAS) is designed to adjust TDE gain online. Prescribed performance control (PPC) method is used to guarantee transient response speed and steady‐state accuracy. Moreover, the transform function of PPC employed in this paper has unlimited domain, which greatly improves the robustness and stability of system. An improved fixed‐time dynamical system is firstly deduced and analyzed, then a new fast nonsingular terminal sliding mode surface is designed to accelerate convergence rate of tracking errors. Finally, the whole system is strictly proven to be practical finite‐time stable, which means that tracking errors can converge to a small neighborhood of zero within a uniformly bounded convergence time. Main advantages of the proposed approach include model‐free, robust, singularity‐free, faster transient response and higher steady‐state tracking precision. Experimental results carried out on the Rethink Sawyer Robot also verified the effectiveness of the proposed scheme.

Fast Finite-Time Path-Following Control for Autonomous Vehicle via Complete Model-Free Approach

Without any knowledge of the vehicle model and its parameters, a novel complete model-free path-following control strategy is developed for autonomous vehicles based on the time-delay estimation (TDE) technique. Different from the existing time-delay control (TDC) approaches, an adaptive nonsingular terminal sliding mode (ANTSM) control law is designed to stabilize the path-following errors without any information of the suitable control gain, which is significant in the conventional TDC scheme, and the boundary of the TDE error, which is necessary for the sliding-mode-based control scheme. The proposed model-free control structure can dynamically update the gain of the designed controller and the boundaries of the TDE error, and the practical finite-time convergence of the preview error can be achieved. In the HIL tests, the comparative results demonstrate that the proposed ANTSM model-free control strategy can provide superior comprehensive tracking performance over both the model-based sliding mode controller and the conventional TDC controller, while the autonomous vehicle follows desired paths.

Reinforcement Learning-Based Adaptive Position Control Scheme for Uncertain Robotic Manipulators with Constrained Angular Position and Angular Velocity

Aiming at robotic manipulators subject to system uncertainty and external disturbance, this paper presents a novel adaptive control scheme that uses the time delay estimation (TED) technique and reinforcement learning (RL) technique to achieve a good tracking performance for each joint of a manipulator. Compared to conventional controllers, the proposed control scheme can not only handle the system parametric uncertainty and external disturbance but also guarantee both the angular positions and angular velocities of each joint without exceeding their preset constraints. Moreover, it has been proved by using Lyapunov theory that the tracking errors are uniformly ultimately bounded (UUB) with a small bound related to the parameters of the controller. Additionally, an innovative RL-based auxiliary term in the proposed controller further minimizes the steady state tracking errors, and thereby the tracking accuracy is not compromised by the lack of asymptotic convergence of tracking errors. Finally, the simulation results validate the effectiveness of the proposed control scheme.

Trajectory tracking control of a coaxial rotor drone: Time-delay estimation-based optimal model-free fuzzy logic approach

This paper proposes a control algorithm for controlling the position and attitude of a coaxial rotor drone without knowing the model dynamics. To overcome the major drawback of model-dependent approaches, an optimal model-free fuzzy controller (OMFFC) based on the estimation of the unknown dynamic function of the system is proposed. A time-delay estimation (TDE) technique is effectively exploited to approximate the unknown dynamic function of the system. The estimation error is then offset using a robust adaptive fuzzy logic compensator. Based on Lyapunov stability arguments, the global asymptotic stability of the coaxial rotor drone system is proven. Moreover, a flower pollination-based algorithm is also proposed to generate the optimal parameters to address the trade-off between optimal tracking performance and the design conditions related to the closed-loop stability requirements. The numerical simulations illustrate how the proposed methodology leads to the best performance, as well as less computational complexity compared to the standard proportional–integral–derivative and time-delay estimation-based controllers in the presence of external disturbances.

Finite time fractional order ISMC with time delay estimation for re-entry phase of RLV with enhanced chattering suppression

This paper investigates the attitude controller design for the reusable launch vehicle (RLV) in its re-entry phase under the influence of model uncertainties and external disturbances. The navigation of RLV along a predefined safe trajectory is a challenging task since the RLV system dynamics has a complex nonlinear behaviour with uncertain environmental conditions. Therefore, this paper proposes a time-delay estimation technique with fractional order integral sliding mode control abbreviated as FOISMC-TDC, for efficient tracking of a pre-designed reference trajectory that ensures safe landing of the RLV. The time delay estimation method in the proposed research employs the input–output information of the immediate past instant to estimate any uncertainties and un-modelled dynamics. The estimated value is then fed to the composite control for disturbance compensation without primarily relying on the switching control of FOISMC approach. This in turn, eliminates the problem of high-frequency chattering in the control input. In addition, by using FOISMC philosophy finite time convergence of system states is achieved with desired error response. Furthermore, Lyapunov and homogeneity theories have been utilized to establish practical finite-time stability of the overall closed loop system. Numerical analysis with state-of-the-art techniques have also been presented to demonstrate effectiveness of the proposed methodology.

An Adaptive Finite-Time Force-Sensorless Tracking Control Scheme for Pneumatic Muscle Actuators by an Optimal Force Estimation

The prime challenges of the force control generated by pneumatic muscle actuators (PMAs) have arisen from their highly nonlinear properties, which are perturbed by dynamic uncertainties and external disturbances. To achieve fast response, high accuracy, and robust force tracking performance without using a force sensor, this letter proposes an adaptive finite-time force-sensorless control scheme for a single-joint manipulator configured by a pair of antagonistic PMAs. First, a newly time-varying adaptive optimal force estimation scheme is proposed to obtain the environmental contact force using only position information, such that improvements of transient response and estimated accuracy are assisted by the cost function of the predefined estimation error. Next, the principal control method relied on core elements of a finite-time integral fast terminal sliding mode control procedure is developed. Additionally, a force-based time delay estimation technique is deployed to estimate the lumped uncertainties. Meanwhile, the new adaptive gain law assists in compensating for the remained error of the estimator. The stability and finite-time convergence features of the whole system are demonstrated through Lyapunov theory. Finally, a series of trials are conducted on an actual paradigm with an adjustable environment configuration. The reliability and superiority of our approach are confirmed by comparing the experimental results with other approaches.

Model‐free incremental adaptive dynamic programming based approximate robust optimal regulation

AbstractThis article presents a new formulation for model‐free robust optimal regulation of continuous‐time nonlinear systems. The proposed reinforcement learning based approach, referred to as incremental adaptive dynamic programming (IADP), utilizes measured input‐state data to allow the design of the approximate optimal incremental control strategy, stabilizing the controlled system incrementally under model uncertainties, environmental disturbances, and input saturation. By leveraging the time delay estimation (TDE) technique, we first use sensor data to reduce the requirement of a complete dynamics, where input‐state data is adopted to construct an incremental dynamics which reflects the system evolution in an incremental form. Then, the resulting incremental dynamics serves to design the approximate optimal incremental control strategy based on adaptive dynamic programming, which is implemented as a simplified single critic structure to get the approximate solution to the value function of the Hamilton–Jacobi–Bellman equation. Furthermore, for the critic neural network, experience data are used to design an off‐policy weight update law with guaranteed weight convergence. Rather importantly, we incorporate a TDE error bound related term into the cost function, whereby the unintentionally introduced TDE error is attenuated during the optimization process. The proofs of system stability and weight convergence are provided. Numerical simulations are conducted to validate the effectiveness and superiority of our proposed IADP, especially regarding the reduced control energy expenditure and the enhanced robustness.

Under-ice target echo time delay estimation using [formula omitted]-norm based matched filter

In the ice-covered underwater environment of the Arctic area, impulsive noise is one of the most challenging problems for target echo time-delay estimation (TDE) and severely degrades the performance of some so-called traditional TDE algorithms. In this work, we propose a TDE approach called “ℓp-norm-based correlation,” which is explored for use in active sonar systems in an impulsive environment. The ℓp-norm-based optimization is presented here to improve the robustness, and we introduce the Toeplitz matrix to formulate the received signal. The different columns of the desired matrix represent the various time-delay replicas of the transmitted signal, and the global minimizer can be found by rewriting the optimization problem. Thus, all global minimizers are efficiently solved simultaneously. The proposed TDE technique can enhance time-delay resolution and provide reliable estimation results compared with conventional matched filtering and other competing approaches. Furthermore, we show that the performance of the resulting method can be verified by the results of numerical simulation and by comparison with the experimental data collected from the 11th Chinese National Arctic Research Expedition.

Barrier Function-Based Adaptive Sliding Mode Control for Application to Vehicle Suspensions

A barrier function-based adaptive sliding mode control (SMC) strategy is proposed for the vehicle active suspension system in this article. The barrier function-based adaptive law is applied to design the sliding mode controller, which can ensure the finite-time convergence of the suspension system. Meanwhile, the proposed adaptive law can achieve greatly chattering reduction without requiring the prior information of the upper bound of system uncertainties. Furthermore, the time-delay estimation technique is applied to design the simple and efficient model-free controller. Therefore, the proposed controller has the strong robustness against the nonlinearities and uncertainties of the active suspension system, and it is very practical in actual scenarios. In addition, considering the transient and steady-state performance of the active suspension system, a prescribed performance function is adopted to constrain the vehicle displacement with its convergence rate, maximum overshoot, and steady-state value. Finally, compared with the conventional SMC and PD control, comparative experiments of a quarter-car active suspension platform are performed to verify the effectiveness of the proposed strategy.

Model-free adaptive sliding mode control with adjustable funnel boundary for robot manipulators with uncertainties.

Considering that the nominal dynamics model or numerous parameters of robotics are usually unsuitable for real applications, a model-free adaptive sliding mode control with an adjustable funnel boundary is proposed for robot manipulators with uncertainties. First, time delay estimation (TDE) technique is utilized to estimate the unknown dynamics of the control system, which ensures an attractive model-free advantage. Furthermore, a modified funnel function is introduced to transform the trajectory tracking error fall within an adjustable funnel boundary strictly. Then, based on the transformed error variable, a novel funnel nonsingular fast terminal sliding mode control scheme is developed to enhance the transient and steady-state tracking performance of the closed-loop control system. To cope with the TDE error, an adaptive update method is designed with only one adaptive parameter, which is adaptively tuned according to the sliding surface. Finally, the simulation and experimental results are presented to illustrate the superiority and high-precision tracking performance of the proposed approach.

Model‐free finite‐time terminal sliding mode control with a novel adaptive sliding mode observer of uncertain robot systems

AbstractThis paper presents a model‐free finite‐time terminal sliding mode control scheme of uncertain robot systems. Time delay estimation (TDE) technique is employed to estimate mathematical model of system. However, TDE cannot achieve satisfactory performance when the system suffers from impactive disturbances. For this reason, a novel adaptive sliding mode observer is designed to compensate estimation errors. Moreover, the proposed observer is finite‐time stable and the design process does not depend on the upper bounds of uncertainties and its derivatives, and it can be also extended to other nonlinear systems with external disturbance. A nonsingular fast terminal sliding surface is designed to accelerate convergence rate and boundary layer technique is adopted to attenuate the chattering phenomenon. Finally, a finite‐time stable controller is constructed to stabilize the closed‐loop system. The proposed controller is model‐free and can be easily implemented in practice. The stability of both observer and controller is strictly proven in the Lyapunov framework. Simulations and experimental studies using Rethink Sawyer Robot are carried out to verify the effectiveness of the proposed scheme.