Time-delay Method Research Articles

Vibration control of MR whole-spacecraft under medium–high frequency and small amplitude considering actuator time-delay

The satellite bears complex vibration loads transmitted from the satellite-rocket interface during launch, where medium–high frequency and small amplitude vibration is highly likely to harm the satellite’s internal precision instruments. Under such special conditions, the time-delay factor of the MR damper as the actuator cannot be ignored in the vibration control of the magnetorheological (MR) whole-spacecraft. To compensate actuator time-delay, and consider the system’s nonlinear characteristics under medium–high frequency and small amplitude conditions, a gray prediction time-delay compensation method is proposed based on the human-simulated intelligent controller (HSIC). After verifying through simulation and experiment that actuator time-delay affects the vibration response of the MR whole-spacecraft, the HSIC based on gray prediction is designed. Then, the control effect of HSIC with or without time-delay is simulated numerically. The results reveal that after considering the time-delay factor, the resonance peak increases by 17%, and the transmissibility of the concerned particularly frequency band (40 Hz) increases by 62%, which implies a significant deterioration in the control effect. Following, to make up for the response deterioration caused by the time-delay, the HSIC based on gray prediction is used for numerical simulation. The results confirm that reasonable time-delay compensation can effectively improve the system dynamics. This study provides a reference for the practical application of the whole-spacecraft controller.

Natural Gas–Electricity Price Linkage Analysis Method Based on Benefit–Cost and Attention–VECM Model

In recent years, frequent linkage events of natural gas and electricity prices have seriously affected the stability of the energy supply market. In view of the increasingly close linkage relationship between gas and electricity prices, a gas–electricity price linkage analysis method considering the benefit–cost and price transmission of gas units is proposed. Firstly, a benefit–cost model of gas units based on risk premium theory is constructed to reflect the willingness of gas units to offer prices in different market environments. Secondly, a vector error correction model (VECM)-based gas–electricity price conduction analysis method was proposed to study the long-term co-integration relationship between gas–electricity prices and the short-term fluctuation conduction process. Then, aiming at the problem of delay in price transmission, a time-delay analysis method of gas–electricity price based on the attention mechanism is proposed. Finally, the gas price index and average gas power price data of China from August 2020 to November 2022 are used to verify the validity of the proposed model; the numerical results show that the proposed method can determine the long-term stable fitting relationship between gas and electricity prices, and can also analyze and judge the conduction direction of gas and electricity price fluctuations in different time periods.

Control of chaos with time-delayed feedback based on deep reinforcement learning

The time-delayed feedback control method, as one of popular methods for chaos control, is noninvasive and flexible for various dynamical systems from different fields of science and technology. In the method, however, an appropriate choice of the feedback gain is challenging, which requires the explicit mathematical model of the controlled system for stability analysis. Additionally, another limitation of the method is the so-called odd number limitation. The two problems restrict its application to practical situations. Fortunately, a technique called deep reinforcement learning is capable of learning the controlled environment (the dynamical system), by continually interacting with the controlled system, which makes it possible to obtain the right feedback gain without the requirement of the accurate mathematical model of the system. Hence, in this work, a time-delayed feedback control method based on deep reinforcement learning is put forward to solve the two problems. Compared with the traditional time-delayed feedback control, the proposed method, as a data-driven method due to the combination with deep reinforcement learning, offers a time-varying feedback gain according to the well-trained policy learned by the deep reinforcement learning algorithm. It maintains the non-invasive property of the time-delayed feedback control, but expands the operating range due to the time-varying feedback gain overcoming the odd number limitation. With numerical simulations, the proposed method is successfully applied to three different kinds of systems, the discrete logistic map, the non-autonomous Duffing oscillator and the autonomous Lorenz system.

Synchronization Analysis of Fractional Order Delayed BAM Neural Networks via Multi-Delay-Boundary Inequality

This paper analyzes the synchronization of Caputo fractional-order BAM neural networks with multiple time-varying delays (FOBAMNNs-MTDs). The time-delay phenomenon is inevitable in the synchronization process. Thereby, it is crucial to fully consider the time-delay information on behalf of better studying the synchronization problem. In previously published studies of Caputo FOBAMNNs-MTDs, the time-delay information of bounded MTDs is implied in the delayed state term. Then, the boundary information of MTDs is not considered by applying the method mentioned above, which will be detrimental to the accuracy of the system dynamic characteristics analysis. This paper aims to propose a new time-delay information processing method to enhance the utilization of MTD information, thereby improving the synchronization analysis of FOBAMNNs-MTDs. Firstly, an inequality called multi-delay-boundary inequality (MDBI) containing all boundary information of time-varying delays and fractional-order information is proposed. That is, a new time-delay information processing method of MTDs with different boundary information is proposed, which makes full use of MTD information. Secondly, a less-conservatism synchronization criterion with the information of all delay boundary and fractional-order of Caputo FOBAMNNs-MTDs is established, which is more flexible than the delay-independent criterion. Finally, two numerical simulations are provided to verify the validity of the obtained results.

Characterisations of self-excited nonlinear oscillations at varied system parameters in a Rijke tube with a premixed laminar flame

Thermoacoustic instability has been one of the major concerns in various industrial combustion systems, such as Rich burn, Quick mix, Lean burn engine and aerospace engines. The complex interactions between heat release and pressure fluctuations could generate thermoacoustic oscillations with high amplitudes and frequencies in a combustion chamber, which causes many combustion problems even severe structural damage. The studies about the effects of various system parameters on thermoacoustic instability would be important due to their crucial roles in characterising the system oscillations. In this study, the effects of different system parameters in a Rijke tube, including equivalence ratio, methane flowrate, burner position and tube inner diameter, have been investigated. The time-domain analysis methods, including both phase space analysis constructed from the time-delayed method and recurrence analysis, have been conducted to explore the system characteristics under different system parameters. Furthermore, the Recurrence Quantitative Analysis (RQA) and Wayland translation error have been processed to quantify the system nonlinearity. The study has shown the effects of system parameters on system frequency response, deterministic nature and nonlinear dynamics. The system oscillation tends to be more complex and unstable when the burner is moved to lower positions or in a large diameter tube. The phase space and recurrence analysis are found to be efficient for characterising the system nonlinearity with useful insights of self-excited thermoacoustic oscillations.

TDCOSMO

We have measured the redshifts and single-aperture velocity dispersions of eight lens galaxies using the data collected by the Echellette Spectrograph and Imager (ESI) and Low Resolution Imaging Spectrometer (LRIS) at W.M. Keck observatory on different observing nights spread over three years (2018–2020). These results, combined with other ancillary data, such as high-resolution images of the lens systems, and time delays, are necessary to increase the sample size of the quasar-galaxy lens systems for which the Hubble constant can be measured, using the time-delay strong lensing method, hence increasing the precision of its inference. Typically, the 2D spectra of the quasar-galaxy lens systems get spatially blended due to seeing by ground-based observations. As a result, the extracted lensing galaxy (deflector) spectra become significantly contaminated by quasar light, which affects the ability to extract meaningful information about the deflector. To account for spatial blending and extract less contaminated and higher signal-to-noise ratio (S/N) 1D spectra of the deflectors, a forward modeling method has been implemented. From the extracted spectra, we have measured redshifts using prominent absorption lines and single aperture velocity dispersions using the penalized pixel fitting code pPXF. In this paper, we report the redshifts and single aperture velocity dispersions of eight lens galaxies – J0147+4630, B0445+123, B0631+519, J0659+1629, J0818−2613, J0924+0219, J1433+6007, and J1817+2729. Among these systems, six do not have previously measured velocity dispersions; for the other two, our measurements are consistent with previously reported values. Additionally, we have measured the previously unknown redshifts of the deflectors in J0818−2613 and J1817+2729 to be 0.866 ± 0.002 and 0.408 ± 0.002, respectively.

Stability analysis of hybrid stochastic delay differential equations with asynchronous switching and discrete observations

AbstractThis paper studies the hybrid stochastic delay differential equations (SDDEs) with asynchronous switching and discrete observations. For SDDEs based on discrete observations, there are two methods: The discrete‐time approach and the input time delay method. For linear solvable equations, the discrete‐time approach is feasible but for unsolvable nonlinear hybrid SDSs, the results of the discrete‐time approach have not been discussed. So, it is natural to ask: Is the discrete‐time approach still workable for nonlinear hybrid SDSs? This paper focuses on this problem. By using tools of stochastic analysis, constructing Lyapunov functional and using the discrete‐time approach, the stability of hybrid SDSs by discrete‐time feedback control is obtained. Finally, a numerical example is presented to verify the theoretical result.

A method and its validation for measuring the absolute time-delay of the read-out system of a space electrostatic accelerometer.

High-precision accelerometers play an important role in satellite gravity field missions to measure the non-conservative forces acting on the satellites. To map the Earth's gravity field, the accelerometer data must be time-tagged using the on-board global navigation satellite system time reference. For example, in the Gravity Recovery and Climate Experiment mission, the time-tag error of the accelerometers must be within 0.1ms with respect to the satellite clock. To realize this requirement, the time delay between the actual measurement time and the nominal time of the accelerometer should be considered and corrected. This paper presents the techniques for measuring the absolute time delay of an electrostatic accelerometer on the ground, where this delay is mainly introduced by the low-noise scientific data read-out system, which is based on a Σ-Δ (sigma-delta) analog-to-digital converter (ADC). First, the time-delay sources of the system are theoretically analyzed. Then, a time-delay measurement method is proposed, and its principle and system error are presented. Finally, a prototype is built to demonstrate and investigate the feasibility of the method. Experimental results show that the absolute time delay of the read-out system is 150.80 ± 0.04ms. This important value is the basis for the final time-tag error correction of the scientific accelerometer data. Meanwhile, the time-delay measurement method described in this paper is also useful for other data acquisition systems.

The role of the fitness model in the suppression of neuronal synchronous behavior with three-stage switching control in clustered networks

In this work, we investigate the synchronization of neuronal activity through a model of a clustered network formed by scale-free subnetworks. These simulate the areas of the cerebral cortex and capture the spatial distribution of the vertices. The growth of the scale-free subnetworks takes place according to the fitness model, and the architecture of the clustered network presents internal and external links to simulate connections inside and between cortical areas. The corticocortical connections are established according to a human connectivity matrix obtained through experimental data. The model also considers electrical and chemical synapses. A two-dimensional map, in the bursting regime, simulates the dynamic behavior of the neuron. The high synchronization of neuronal activity is revealed by the Kuramoto order parameter. To corroborate the analyses using the order parameter, we calculate a suppression measure. In order to suppress this synchronization, we propose a three-stage switching control as a function of the delayed mean-field in each subnetwork. This suppressor agent is effective in two scenarios, whether applied according to the spatial distribution of neurons or in the emitting hubs of the subnetworks. Our results show that the fitness model has a relevant role in the study of neuronal activity suppression, allied to the application of a three-stage switching control by means of a time-delayed feedback method being an efficient way to suppress synchronization in clustered networks.

Development of Multilayer Transducer and Omnidirectional Reflection Model for Active Reflection Control.

Underwater detection is accomplished using an underwater ultrasonic sensor, sound navigation and ranging (SONAR). Stealth to avoid detection by SONAR plays a major role in modern underwater warfare. In this study, we propose a smart skin that avoids detection by SONAR via controlling the signal reflected from an unmanned underwater vehicle (UUV). The smart skin is a multilayer transducer composed of an acoustic window, a double-layer receiver, and a single-layer transmitter. It separates the incident signal from the reflected signal from outside through the time-delay separation method and cancels the reflected wave from the phase-shifted transmission sound. The characteristics of the receiving and transmitting sensors were analyzed using a finite element analysis. Three types of devices were compared in the design of the sensors. Polyvinylidene fluoride (PVDF), which had little effect on the transmitted sound, was selected as the receiving sensor. A stacked piezoelectric transducer with high sensitivity compared to a cymbal transducer was used as the transmitter. The active reflection control system was modeled and verified using 2D 360° reflection experiments. The stealth effect that could be achieved by applying a smart skin to a UUV was presented through an active reflection-control omnidirectional reflection model.

Effects of time delay and blood storage methods on analysis of canine venous blood samples with an Element point-of-care analyzer.

Manufacturers of point-of-care (POC) analyzers recommend immediate processing and anaerobic collection of blood samples. However, it is not uncommon for clinical scenarios to result in delayed sample processing or room air exposure that could impact the test results. To investigate the effect of time delay and sample storage method on key POC analytes in canine venous blood samples processed with an Element POC analyzer. Blood gas analysis was performed on venous blood samples at times 0 (T0), 15, 30, and 60 minutes after sampling using three different storage methods: preheparinized plastic syringes and two different lithium heparin tubes. To determine clinical relevance, results were compared with allowable total error of the respective parameter. Significance was set at P < 0.05. Significant differences between the three storage methods at baseline were found for partial pressure of carbon dioxide (PCO2 ), partial pressure of oxygen (PO2 ), base excess, and total hemoglobin. No significant differences up to T60 were found within collection methods for actual bicarbonate (HCO3 - ), base excess, sodium, potassium, chloride, ionized calcium (iCa), glucose, and BUN. Significant differences within collection methods were found after T0 for creatinine, after 15 minutes for lactate, and after 30 minutes for pH and hematocrit. No significant differences were found for PO2 in samples stored in preheparinized plastic syringes at any time point. These results suggest that HCO3 - , sodium, potassium, chloride, iCa, glucose, and BUN are comparable within the three storage methods for up to 60 minutes after sampling without resulting in clinically relevant changes.

A novel data-driven time-delay attack evaluation method for wide-area cyber–physical smart grid systems

One of the main challenges in information and communication technology, as well as wide-area power system researches, is the inability to stabilize the voltage and frequency for cyber–physical power systems under the communication time-delay. Thus, it is imperative to investigate the stochastic characteristics and quantitative method of time-delay. In this paper, a novel data-driven time-delay evaluation method for cyber–physical smart grid systems is proposed. The cyber layer and physical components in wide-area power systems are modeled. The transmitted process of the data packet in a cyber layer is considered, and the probability distribution function of multiple latencies in the spatial sequence is depicted by using M/M/1 queuing theory and signal convolution methods. The Sklar’s theorem and Copula’s theory are utilized to integrate distribution functions of multiple delays into a novel delay quantitative model. Furthermore, the time delay is divided according to the reason of its generation as two parts: (1) inherent delay by nature, and (2) delay caused by network attacks. Various sizes of delays caused by cyber-attacks are detected by using communication principle and likelihood ratio. Finally, the case studies under various scenarios are carried out on the New England ten-machine power system. The simulation results show that the stochastic latencies obey the proposed delay distribution model with probability 99.9%. The comparative results illustrate the mean-square error between the proposed and actual delay distribution probability function as 10−4. The delay caused by cyber-attacks can be separated from nature latency with the threshold η=0.0101.

Simulation and Experimental Research on Time Varying Delay Feedback Control Under Random Excitation

In this paper, the dynamic vibration absorber considering time delay is taken as the research object, and the effect of time delay on the vibration characteristics of the dynamic vibration absorber is studied by combining theory and experiment. In this paper, a time-varying time-delay feedback control method is proposed. Firstly, the instantaneous frequency of complex excitation is obtained by wavelet analysis. The instantaneous frequency determines the critical time-delay parameters of the dynamic vibration absorber with time-delay as the time-delay control quantity. Then, the optimal fixed time-delay feedback gain is calculated by improved particle swarm optimization. Finally, the time-varying delay gain parameter controls the time-delay dynamic vibration absorber. The vibration reduction effect of this approach under complicated excitation is investigated using a 2-DOF vibration system with a time-delay dynamic vibration absorber as an example. Based on simulation calculation, the bench test of the control strategy is carried out, and the influence of the control strategy on the control dynamic characteristics of the primary system is analyzed. The simulation and experimental results are consistent, laying the groundwork for this paper’s research on time-varying delay control.

Active control of vehicle interior engine noise using a multi-channel delayed adaptive notch algorithm based on FxLMS structure

A multi-channel delayed adaptive notch algorithm based on the filtered-x least mean square (FxLMS) structure was proposed for active control of vehicle interior engine noise with prominent harmonic characteristics. First, a complete reference signal model was established utilizing vehicle engine speed. Second, the algorithm procedure was presented systematically, and a new time-delay method was introduced to simplify the filtering process of the reference signal to greatly improve the calculation efficiency. Furthermore, the convergence condition was derived, and mathematical models of the steady-state error and convergence speed were obtained. The simulation results, which were consistent with theoretical calculation values, showed that the two models were highly accurate. They help to theoretically indicate the interval range of the effective convergence coefficient μ and its optimal value. Using the proposed multi-channel delayed adaptive notch algorithm, actual vehicle active noise control experiments were conducted. The results show that, under stationary conditions, the interior overall engine noise reduction in the time-domain reaches 4.05 dB (A), and the corresponding second-order engine noise reduction reaches 13.66 dB (A), however, under nonstationary working conditions, the proposed algorithm still has a good noise reduction effect. This algorithm can be directly applied to the active control of vehicle engine noise and other similar narrowband noise reduction.

Model based development of temperature control schemes for fighter aircraft ECS

The performance of Temperature Control System (TCS), a sub-system of an advanced fighter ECS (Environmental Control System) is studied for its operations both in on-ground and in-air conditions. The standard Bootstrap air cycle system is considered with ACM (Air Cycle Machine) as the main component, which consists of a compressor and a turbine, to produce the cold air. ECS, in particular TCS, is responsible in maintaining the required cockpit or cabin temperature. As the fighter aircraft doesn’t require cabin air recirculation, the cabin temperature depends solely on the supply air thermal conditions. The cabin temperature regulation is realized by controlling the supply conditions by maintaining required temperature at ACM outlet and at the entrance duct to the cabin. These temperatures are critical parameters that necessitates appropriate controller to keep the cabin in a good comfortable state. ECS of a fighter aircraft is highly complex and nonlinear than commercial aircraft. The control logics applied, on this system, will drive the actuators or TCVs (Temperature Control Valves) to keep the requisite cabin temperature. The control logics applied on the controller to be simple and appropriate to meet the requirements of fighter aircraft ECS. This shall minimize the control cycle oscillation and subsequent supply air temperature instabilities. This paper explains novel cabin temperature control schemes and their influence on the ECS performance especially during the transient operation. The complete architecture of the control schemes along with system components are modelled in AMESim and the comparison is made for different operating conditions. Finally, a novel variable time-delay based method to control the cabin supply air temperature is proposed.

TDCOSMO

The largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of H0. A Bayesian hierarchical framework has been proposed which combines lens systems with kinematic data, constraining the mass profile shape at a population level. The framework has been previously validated using a small sample of lensing galaxies drawn from hydro-simulations. The goal of this work is to expand the validation to a more general set of lenses consistent with observed systems, as well as confirm the capacity of the method to combine two lens populations: one which has time delay information and one which lacks time delays and has systematically different image radii. For this purpose, we generated samples of analytic lens mass distributions made of baryons+dark matter and fit the subsequent mock images with standard power-law models. Corresponding kinematics data were also emulated. The hierarchical framework applied to an ensemble of time-delay lenses allowed us to correct the H0 bias associated with model choice to find H0 within 1.5σ of the fiducial value. We then combined this set with a sample of corresponding lens systems which have no time delays and have a source at lower z, resulting in a systematically smaller image radius relative to their effective radius. The hierarchical framework has successfully accounted for this effect, recovering a value of H0 which is both more precise (σ ∼ 2%) and more accurate (0.7% median offset) than the time-delay set alone. This result confirms that non-time-delay lenses can nonetheless contribute valuable constraining power to the determination of H0 via their kinematic constraints, assuming they come from the same global population as the time-delay set.

Analysis and comparison of two methods for reducing the impact of time delay on inverter stability

To more effectively select the method that reduces the impact of time delay in digital control on inverter stability and improve the robustness of an inverter, a discrete model of the inverter with inverter-side current feedback control is first established in the two-phase stationary frame in this paper. Then, based on this model, systematic study is carried out on the inverter stability under half sampling time delay method and linear predictor method respectively. It is found that, compared with one sampling time delay method, half sampling time delay method and linear predictor method are both able to reduce the influence of time delay on inverter stability. Moreover, analysis shows that half sampling time delay method have a better performance than linear predictor method. Finally, experiment results are presented to prove the correctness of theoretical analysis.

Finite frequency domain H ∞ consensus control of neutral multi-agent systems with input delay

The finite frequency domain consensus control problem of neutral multi-agent systems with the input delay is investigated in this paper for the first time. According to the linear transformation, the problem of consensus is converted into a set of stability problems. Through the Lyapunov theory, combined with the time-delay interval decomposition method, a less conservative controller design method for the state feedback controller is presented. And the obtained controller can ensure closed-loop multi-agent systems to fulfil the consensus. Utilizing the generalised Kalman-Yakubovich-Popov (GKYP) lemma, the sufficient condition is derived for multi-agent systems achieving the performance in the finite frequency domain (FFD). Then, via the orthogonal spatial information of the input matrix, the conservativeness of obtained design approach is further declined. Moreover, the design method with less conservativeness is proposed for the dynamic output feedback controller. Finally, a numerical case and a multi-pendulum system controlled by the multi-motor system are presented in this paper to demonstrate the availability and applicability of the proposed methods.

Mechanical Compliance of Individual Fractures in a Heterogeneous Rock Mass From Production‐Type Full‐Waveform Sonic Data

AbstractThe mechanical fracture compliance is of interest in a number of geoscientific applications. Seismic borehole methods, especially full‐waveform sonic (FWS) data, have indicated their potential to infer the compliance of macroscopic fractures under in situ conditions. These approaches rely on the assumption of a homogeneous background embedding the fractures and, as of yet, compliance estimates for individual fractures are limited to static FWS measurements. In this work, we assess the potential of inferring the compliance of individual fractures from standard, production‐type FWS data in the presence of background heterogeneity. We first perform a comparative test on synthetic data to evaluate three approaches known as the transmission, phase, and group time delay methods. The results indicate that the former two produce adequate compliance estimates for scenarios with a strongly heterogeneous background or a damage zone around the fracture. These two methods are then applied to two FWS data sets acquired before and after a hydraulic stimulation campaign in a crystalline rock, which allows to test them on natural and man‐made fractures. The transmission method turned out to be unsuitable for the considered data due to its reliance on amplitudes. Conversely, the travel time behavior remained stable and the phase time delay method produced robust and consistent estimates. The results for a newly created hydro‐fracture imply the capability of resolving remarkably small compliance values of the order of 10−14 m/Pa. This estimate is one order‐of‐magnitude smaller than that for the natural fracture, which may help to distinguish between these two fracture types.

Gene Regulatory Identification Based on the Novel Hybrid Time-Delayed Method.

Gene regulatory network (GRN) inference with biology data is a difficult and serious issue in the field of system biology. In order to detect the direct associations of GRN more accurately, a novel two-step GRN inference technique based on the time-delayed correlation coefficient (TDCC) and time-delayed complex-valued S-system model (TDCVSS) is proposed. First, a TDCC algorithm is utilized to construct an initial network. Second, a TDCVSS model is utilized to prune the network topology in order to delete false-positive regulatory relationships for each target gene. The complex-valued restricted additive tree and complex-valued differential evolution are proposed to approximate the optimal TDCVSS model. Finally, the overall network could be inferred by integrating the regulations of all target genes. Two real gene expression datasets from E. coli and S. cerevisiae gene networks are utilized to evaluate the performances of our proposed two-step GRN inference algorithm. The results demonstrated that the proposed algorithm could infer GRN more correct than classical methods and time-delayed methods.