Fading Measurements Research Articles

The Dynamic Event-Based Non-Fragile H∞ State Estimation for Discrete Nonlinear Systems with Dynamical Bias and Fading Measurement

The present study investigates non-fragile H∞ state estimation based on a dynamic event-triggered mechanism for a class of discrete time-varying nonlinear systems subject to dynamical bias and fading measurements. The dynamic deviation caused by unknown inputs is represented by a dynamic equation with bounded noise. Subsequently, the augmentation technique is employed and the dynamic event-triggered mechanism is introduced in the sensor-to-estimator channel to determine whether data should be transmitted or not, thereby conserving resources. Furthermore, an augmented state-dependent non-fragile state estimator is constructed considering gain perturbation of the estimator and fading measurements during network transmission. Sufficient conditions are provided based on Lyapunov stability and matrix analysis techniques to ensure exponential mean-square stability of the estimation error system while satisfying the H∞ disturbance fading level. The desired estimator gain matrix can be obtained by solving the linear matrix inequality (LMI). Finally, an example is presented to illustrate the effectiveness of the proposed method for designing estimators.

Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell

Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies help to better understand and model degradation and to optimize the operating strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications. To our knowledge, the dataset1 presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for more than a year under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to cells. The dataset1 includes result data (such as the remaining usable capacity or impedance measured in check-ups) and raw data (i.e., measurement logs with two-second resolution). The data can be used in a wide range of applications, for example, to model battery degradation, gain insight into lithium plating, optimize operating strategies, or test battery impedance or state estimation algorithms using machine learning or Kalman filtering.

Distributed fusion filtering for multi-sensor nonlinear networked systems with multiple fading measurements via stochastic communication protocol

This paper studies the distributed fusion filtering (DFF) issue for a class of nonlinear delayed multi-sensor networked systems (MSNSs) subject to multiple fading measurements (MFMs) under stochastic communication protocol (SCP). The phenomenon of MFMs occurs randomly in the network communication channels and is characterized by a diagonal matrix with certain statistical information. In order to decrease the overload of communication network and save network resources, the SCP that can regulate the information transmission between sensors and estimators is adopted. The primary aim of the tackled problem is to develop the DFF method for nonlinear delayed MSNSs in the presence of MFMs and SCP based on the inverse covariance intersection fusion rule. In addition, the local upper bound (UB) of the filtering error covariance (FEC) is derived and minimized by means of suitably designing the local filter gain. Moreover, the boundedness analysis regarding the local UB is proposed with corresponding theoretical proof. Finally, two simulation examples with comparative illustrations are given to display the usefulness and feasibility of the derived theoretical results.

Depletion of Electrolyte Salt Upon Calendaric Aging of Lithium-Ion Batteries and its Effect on Cell Performance

The trend for increased nickel content in layered transition metal oxide cathode active materials and increasing charging cut-off voltages aggravates aging of lithium-ion battery cells at high state of charge (SOC). We investigate the calendaric aging behavior of large-format automotive prototype cells and laboratory single-layer pouch cells at high but realistic cell voltages/SOCs and demonstrate that electrolyte oxidation in combination with follow-up reactions can cause a significant loss of the LiPF6 salt in the electrolyte. For this, we analyze the LiPF6 concentration in aged cells, the generation of H2 upon storage, and the cell resistance for different aging conditions. We show that the LiPF6 loss is a critical aging phenomenon, as it cannot readily be detected by capacity fading measurements at low/medium C-rates or by cell resistance measurements, while it severely reduces rate and fast-charging capability. Under certain circumstances, LiPF6 loss can even lead to a temporary capacity increase due to conversion of the conducting salt in the electrolyte to cyclable lithium in the active material. Finally, we suggest a possible reaction mechanism and a simple accounting model to keep track of how different side reactions involved in LiPF6 loss change the cyclable lithium inventory of a lithium-ion cell.

Synthesis of Alkoxy-TEMPO Aminoxyl Radicals and Electrochemical Characterization in Acetonitrile for Energy Storage Applications

In this paper, we describe the synthesis and characterization of alkoxylated TEMPO, (2,2,6,6-tetramethylpiperidin-1-yl)oxyl, radicals with potential application in organic non-aqueous redox flow batteries. The behavior of a series of TEMPO derivatives with varying lengths of alkoxy chain is analyzed in acetonitrile solutions using electrochemical techniques, electron paramagnetic resonance (EPR) spectroscopy, and measurements of permeability through three different membranes. Electrochemical redox potentials are only weakly dependent on the substituent, but, in contrast, exchange current densities derived from the data do depend on the substitution. EPR lends further insight into these properties via the determination of hyperfine splitting constant and rotational correlation time. There is a negligible effect of the substituents on those parameters among the modified TEMPO radicals. Finally, permeation rates of modified TEMPO derivatives through membranes depend significantly on both the membrane and the substitution of TEMPO, providing insights into capacity fade measurements in the literature.

Distributed Filtering for Networked Stochastic Nonlinear Systems With Fading Measurements and Random Packet Dropouts

Distributed Filtering for Networked Stochastic Nonlinear Systems With Fading Measurements and Random Packet Dropouts

Outlier-Resistant Recursive Security Filtering for Multirate Networked Systems Under Fading Measurements and Round-Robin Protocol

This paper investigates the recursive filtering problem with fading measurements and cyber attacks for multisensor multirate networked systems (MRNSs) under Round-Robin protocol (RRP). By exploiting the lifting technique, the sampling periods for both sensors and the state of the system are uniformed. It is assumed that the phenomenon of fading measurements which better describes practical engineering arises stochastically, and the attenuation coefficients of which are described by a set of random variables with known statistical properties. In order to fully utilize the limited communication resources, RRP is introduced in the sensor-to-filter channel. Considering the measurement outliers, a saturation function is adopted in the filter structure to suppress the anomalous innovations, so as to reduce the negative impact of the outliers. By means of matrix difference equation, an upper bound is first obtained on the filtering error covariance, and the filter gain is designed to minimize the obtained upper bound by partial derivation. Moreover, the exponential boundedness of the filtering error dynamics is analyzed in the mean square sense. Finally, a numerical simulation example is given to demonstrate the validity of the proposed recursive security filtering scheme.

New characterization and evaluation of BaSO4: Eu as a thermoluminescent radiation dosimeter

Thermoluminescence (TL) dosimetry is used in radiation protection and for measuring absorbed dose to patients in diagnostic radiology and radiotherapy. The main aim of the study herein was to assess the TL properties of BaSO4: Eu nanophosphors following irradiation with low dose γ- and X-rays. BaSO4 phosphors activated with various concentrations of Eu were prepared by the co-precipitation method. The highest radiation sensitivity was obtained for an Eu concentration of 0.5 mol%. The TL properties in terms of glow curve, heating rate, reusability, fading and order of kinetics were studied. Optimized BaSO4: Eu irradiated with doses from 1.25 to 50 mGy displayed a major TL peak at ≈ 220 °C and exhibited a linear response with absorbed dose. The reusability test was performed for ten consecutive irradiations, readings, and annealing cycles, and showed a slight decrease in TL after the first cycle after which it was stabilized. Signal fading measurements were performed for irradiated samples over 50 days, where a signal loss of about 0.14 % per day was observed.

Resilient Coordinated Data-Driven Control of Multiple High-Speed Trains Under Fading Measurements and Denial-of-Service Attacks

The paper investigates the resilient coordinated model free adaptive control (MFAC) problem of multiple high-speed trains (MHSTs) subject to fading measurements and denial-of-service (DoS) attacks, which belongs to a data-driven approach. Firstly, the dynamic model of MHSTs with unknown nonlinear dynamics is linearized into a data-dependent one. Secondly, the faded channels are formulated by the Rice fading model with known statistical property, and the attack strategies are assumed to obey the Bernoulli distributions. Then, the distributed MFAC method is proposed for MHSTs with fixed topology, and the analysis is carried out by using the graph theory. Furthermore, the research is extended to the design of the compensation scheme for fading data and to the MHSTs with time-varying topologies. Finally, the effectiveness of the data-driven controller is studied by a numerical simulation.

Consensus control for multi-rate multi-agent systems with fading measurements: the dynamic event-triggered case

This paper studies the distributed -consensus control problem for a class of multi-rate multi-agent systems with fading measurements. A multi-rate sampling strategy is adopted to be more in line with actual need and the channels between each agent and its sensor always fade non-identically. The multi-rate system is transformed into a single-rate system via the lifting technique. For the purpose of reducing the transmission burden, a dynamic event-triggered mechanism is utilized to determine whether the agent's information is allowed to transmit to its neighbours. This paper aims to design an observer-based event-triggered controller for each agent to achieve the -consensus control performance constraint. With the help of the Lyapuonv stability theory, sufficient conditions are obtained that can ensure the desired control performance for the resulting closed-loop systems, and then the desired gain matrices are calculated by solving the linear matrix inequality. Finally, a numerical simulation example is given to demonstrate the effectiveness of the distributed event-triggered consensus control scheme.

Distributed Kalman filtering over sensor networks with fading measurements and random link failures

This paper investigates the distributed state estimation problem for a linear time-invariant system characterized by fading measurements and random link failures. We assume that the fading effect of the measurements occurs slowly. Additionally, communication failures between sensors can affect the state estimation performance. To this end, we propose a Kalman filtering algorithm composed of a structural data fusion stage and a signal date fusion stage. The number of communications can be decreased by executing signal data fusion when a global estimate is required. Then, we investigate the stability conditions for the proposed distributed approach. Furthermore, we analyze the mismatch between the estimation generated by the proposed distributed algorithm and that obtained by the centralized Kalman filter. Lastly, numerical results verify the feasibility of the proposed distributed method.

Distributed Dimensionality Reduction Fusion Estimation for Stochastic Uncertain Systems With Fading Measurements Subject to Mixed Attacks

In this article, the distributed fusion estimation issue with the dimensionality reduction strategy under DoS attacks and deception attacks is investigated for a class of stochastic uncertain systems with fading measurements. The stochastic uncertainties existed in the system and measurement equations are represented by state-dependent noises. The fading measurements are depicted by stochastic variables with known statistics. Then, a novel attack and compensation model is proposed to display the randomly occurring behaviors of the DoS attacks and the deception attacks within a unified framework. Furthermore, a distributed multisensor fusion estimation (DMSFE) algorithm is presented. An explicit form of dimensionality reduction is designed against attacks. Stability conditions are derived such that the mean square errors (MSEs) of the proposed DMSFE are bounded. A sequential covariance intersection fusion estimator (SCIFE) is designed to prevent the cross fusion covariance matrices calculating, which owns lower accuracy by smaller computation cost than DMSFE. An illustrative example is provided to show the effectiveness and merits of the proposed algorithm.

Nonuniform Sampling Control for Multibody High-Speed Train Systems With Quantization Mechanisms via Stochastic Faded Channels

This paper studies the dissipative control problem of the multibody high-speed train (HST) systems with nonuniform sampling mechanisms and logarithmic quantizers, in which the transmitted signals are subject to random fading phenomenon. The tracking error dynamic model of HST is firstly established and the logarithmic quantizers for both the input and output (I/O) signals are designed. The faded I/O signals are described by the Rice fading model, in which the mathematical expectation and variance are given in advance. Then, based on the Lyapunov-Krasovskii functional approach with the consideration of time-varying delay, sufficient conditions are derived to ensure the convergence of tracking error and that HST is strictly dissipative. Further, the design method of the gain matrix is obtained by employing the linear matrix inequalities (LMI) techniques and a compensation algorithm is designed to offset the adverse effect brought by the fading measurements. Finally, the effectiveness of the proposed controller is verified by a numerical example from Japan Shinkansen HST.

Nonfragile Dissipative Fuzzy PID Control With Mixed Fading Measurements

This article is concerned with the extended dissipative fuzzy proportional–integral–derivative (PID) control problem for nonlinear systems subject to controller parameter perturbations over a class of mixed fading channels. The sensors of plant are divided into two groups according to engineering practice, where the individual sensor group transmits the measurements to the controller via a respective communication channel undergoing specific fading effects. Considering the complicated nature of the signal fading with the transmission channels, two stochastic models (i.e., the independent and identically distributed fading model and the Markov fading model) are simultaneously employed to describe the mixed fading effects of the two communication channels corresponding to the two sensor groups. The objective of this article is to design a nonfragile PID controller such that the closed-loop system is exponentially stable in mean square and extended stochastically dissipative. With the assistance of the Lyapunov stability theory and stochastic analysis method, sufficient conditions are obtained to analyze the system performance. Then, within the established theoretical framework, an iterative optimization algorithm is proposed to design the desired controller parameters by using the convex optimization technique. Finally, two simulation examples are given to verify the effectiveness of the proposed control schemes.

An enhanced optical micro-fading device

This paper introduces a new set-up for the determination of colour change on cultural heritage objects, referred to herein as a stereo-microfading tester. The system uses high quality optics through the implementation of a stereo-microscope as its central element. This technology enables new developments such as incorporation of high quality imaging systems, and separation of fading and colour measurement processes. This paper describes this new micro-fading set-up and evaluates its performance against traditional devices based on the measurement of blue wool standards. The results show a correlation between the fading performance obtained on different devices while highlighting a significant variability inherent to the blue wool samples

Reduced-order filtering for discrete-time singular systems under fading channels

In this paper, the reduced-order filtering problem for discrete-time singular systems under fading channels is studied. Our aim is to design a reduced-order filter to ensure the filtering error system with fading measurements is stochastically admissible and meets the given performance index. And the designed method is less conservative. However, the standard linear matrix inequality (LMI) cannot be obtained due to the nonlinear terms in decoupling. For this purpose, a new LMI is obtained by using new decoupling method. Finally, numerical example and electrical circuit example are given to clearly illustrate that the proposed method is less conservative than that of the existing method.

Resilient Model-Free Adaptive Iterative Learning Control for Nonlinear Systems Under Periodic DoS Attacks via a Fading Channel

This article studies the resilient control problem for a class of unknown nonlinear systems with fading measurements under malicious denial-of-service (DoS) attacks. The system output is assumed to be transmitted through a fading channel, where the fading phenomenon is described by a Rice fading model. The strategy of the attacker is to periodically interfere with the networked channels to reduce the success rate of data transmissions. First, a dynamic linearization method along the iteration domain is introduced to convert the nonlinear system into an equivalent data-related model. Then, a model-free adaptive iterative learning control (MFAILC) scheme is presented, which is independent of model information. The convergence of the MFAILC scheme is deduced theoretically and the influence of DoS attacks and stochastic fading phenomenon on system stability are also analyzed. Finally, the effectiveness of the design is verified by a numerical simulation and a trajectory tracking example of wheeled mobile robots (WMRs).

Multispectral athermal fading rate measurements of K-feldspar

This study reports athermal fading rates in K-feldspar grains extracted from sediments of varied ages and provenances. Multiple combinations of stimulation and emission spectral regions were examined to identify an optimum combination that provides a luminescence signal with minimal athermal fading. Stimulation wavelengths used were IR (855 ± 33 nm), green (525 ± 30 nm), blue (470 ± 20 nm), and violet (405 ± 15 nm), and detection windows were broad-UV (260–400 nm), narrow-UV (327–353 nm), and blue (320–520 nm).Athermal fading rates using a single stimulation and sequential double stimulation combinations were estimated. For single stimulation, the average fading rates (gAV) ranged from 6.6 to 7.9% per decade. Sequential double stimulation comprising post green-blue (pGB), post blue-violet (pBV), post blue-IR (pBIR), and post violet-IR (pVIR) gave fading rates ranging from 2.0 to 0.0% per decade. The minimum fading rate value gAV = 0.0 ± 0.1% per decade was obtained for pVIR stimulation, and this highlights it as a potential candidate for dating sediments such that the tedium and time of fading measurements can be minimized.

Iterative learning guaranteed cost control based on two‐dimensional Roesser systems subject to denial‐of‐service attacks and fading measurements

AbstractIn this article, the network‐based iterative learning guaranteed cost control problem for the linear systems subject to denial‐of‐service (DoS) attacks at input and output (I/O) sides is studied via faded channels. First, the DoS attacks are modeled by independent Bernoulli sequences, where the expectation and variance are known. The fading measurements in I/O channels are described as independent Gaussian distributions with known expectations and variances respectively. Then, the repetitive system and the proposed ILC scheme involving both the iteration and time axes are transformed into a random two‐dimensional (2D) Roesser model by using the 2D system theory. The mean‐square asymptotic stability is introduced and followed by the definition of guaranteed cost function. Next, sufficient conditions that can not only ensure the asymptotic stability but also the cost index are derived. By applying the linear matrix inequality technology, the gain matrices and the upper bound of the control cost are further obtained. After exploring the adverse effect brought by the random fading phenomenon, a compensation algorithm is then designed and the analysis is strictly deduced. Finally, an injection molding process example is given to confirm the validity of the design.

Developing an internally consistent methodology for K-feldspar MAAD TL thermochronology

Luminescence thermochronology and thermometry can quantify recent changes in rock exhumation rates and rock surface temperatures, but these methods require accurate determination of several kinetic parameters. For K-feldspar thermoluminescence (TL) glow curves, which comprise overlapping signals of different thermal stability, it is challenging to develop measurements that capture these parameter values. Here, we present multiple-aliquot additive-dose (MAAD) TL dose–response and fading measurements from bedrock-extracted K-feldspars. These measurements are compared with Monte Carlo simulations to identify best-fit values for recombination center density (ρ) and activation energy (ΔE). This is done for each dataset separately, and then by combining dose–response and fading misfits to yield more precise ρ and ΔE values consistent with both experiments. Finally, these values are used to estimate the characteristic dose (D0) of samples. This approach produces kinetic parameter values consistent with comparable studies and results in expected fractional saturation differences between samples.