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In this paper, a Cucker–Smale model with time-varying heterogeneous delays in the communication process is investigated, where the delay on each communication link is time-varying and independent of other communication links. A general update rule based on the distance between agents is used to determine the edge weights of the communication network. The method of constructing augmented system is used so that the system stability is transformed into a product convergence problem of time-varying sub-stochastic matrices equivalently. By analyzing this convergence problem, a sufficient condition is established to achieve flocking, which relates to the initial states, the structure of communication network and the upper bound of time delays. [ABSTRACT FROM AUTHOR]

Highlights • Novel Lyapunov functions are constructed to investigate the stability analysis. • The RBF Neural Network can approximate the unknown smooth function. • The dynamic surface control technique is applied to eliminate the "explosion of the complexity". • The adaptive backstepping dynamic surface control is proposed for nonlinear system. Abstract This paper develops an adaptive backstepping dynamic surface control method with RBF Neural Network for a class of nonlinear system under extra disturbances. The considered RBF Neural Network based on adaptive control is applied to approximate the unknown smooth function arbitrarily. The "explosion of the complexity" is eliminated by utilizing the dynamic surface control technique. The Lyapunov function is employed to verify the globally asymptotically stability of the control nonlinear system. Four examples were given to show that the novel control method can not only tracking the expected trajectory very well but also has a better approximation capability for various complex unknown smooth function under disturbances. [ABSTRACT FROM AUTHOR]

Abstract A novel deep learning based eddy current inversion algorithm is proposed and investigated in this paper. Eddy current testing (ECT) for defects detection problem is adopted to demonstrated the proposed algorithms. The proposed model based on a Convolutional Neural Network (CNN) is developed to improve the defect detection performance with uncertainty information. The novelty of our work consists in combining characteristics of ECT data with general deep learning model to improve performance of deep learning in ECT field including a region of interest (ROI) method based on robust principle component analysis, a CNN classification model with weighted loss function and measurement of uncertainties. Experimental dataset obtained from eddy current inspection of heat exchanger tubes is utilized to validate the detection performance improvement. As a result, both the classification accuracy and the percentage of defects correctly identified have been increased to almost 100%. [ABSTRACT FROM AUTHOR]

Abstract Magnetic flux leakage (MFL) techniques are widely used for nondestructive testing of ferromagnetic materials. An analytical model of the MFL field is essential for precise determination and reconstruction of defects. In this paper, we proposed a solenoid model based on magnetization mechanisms of the magnetic medium to explain the MFL principle and simulate the MFL field. By introducing the interaction of solenoids and the Jiles–Atherton model, this model can accurately calculate the MFL field of complex defects, particularly the field distortion caused by the coupling of the defect's components. The solenoid model was experimentally demonstrated with a Z-shaped defect in the specimen and proved to be valid for precise calculation of the magneto-optical image. This work reveals the MFL testing principle from the viewpoint of the magnetic medium and thus helps elucidate and eradicate the simulation errors. The more accurate simulation than the common magnetic dipole model facilitates the inverse calculation of defects, even if field distortion is involved. [ABSTRACT FROM AUTHOR]

Highlights • This paper studies the consensus problem of discrete-time heterogeneous multi-agent systems with random link failures and switching topologies. • The properties of the infinite products of time-varying random row-stochastic matrices and graph theory are explored to analyze this problem. • A sufficient condition that only depends on the topology structures is obtained. Abstract In this paper, we consider the issue of consensus among the agents with heterogeneous dynamics under random link failures that obey Bernoulli distribution. The heterogeneous multi-agent systems (MASs) are composed of hybrid dynamic agents including first-order dynamic agents and second-order dynamic agents, and the communication topologies are assumed to be directed and time-varying. The failure control protocol is designed by randomly utilizing the previous one- or two-step states information sent by the neighbors. A criterion for the heterogeneous consensus is established by constructing augmented systems with nonnegative random coefficient matrices for the switching topologies. With the help of graph theory and stochastic matrix theory, a sufficient condition related to switching topologies is established to ensure the realization of heterogeneous consensus. Numerical examples are finally provided to validate the theoretical result. [ABSTRACT FROM AUTHOR]

A crystal oscillator is a typical frequency generating unit that is widely used in computers, neural chips, biosensors and other applications; thus, it is very important to estimate and predict its remaining useful life (RUL) precisely. However, there are few existing RUL prediction methods because the observed data involve various uncertainties, leading to the great limitation of RUL prediction in practical application. In this work, we propose an uncertainty RUL prediction method based on the exponential stochastic degradation model that considers the multiple uncertainty sources of oscillator stochastic degradation processes simultaneously. Next, based on Bayesian theory, a novel Bayesian-Extreme Learning Machine parameter-updating algorithm that combines the local and global similarity methods is presented and used to eliminate the effects of multiple uncertainty sources and predict the RUL accurately. The effectiveness of the method is demonstrated using the accelerated degradation tests of crystal oscillators. Through comparisons with the predicted results without uncertainty, the proposed method demonstrates its superiority in describing the stochastic degradation processes and predicting the oscillator's RUL. [ABSTRACT FROM AUTHOR]

On the basis of the Faraday Magneto-optical Effect (FMoE) method, that the polarized light would rotate its polarizing direction when there is the magnetic in its moving direction, a NDT method based on Magnetic optic imaging (MOI) is proposed to detect and identify the crack. In order to identify the crack, the pulsed-couple neural network (PCNN) model based this method is developed and improved to select the threshold dynamically. The output image of the PCNN model is pulsed image and this kind of image is processed by the magnetic domain spots filter. This kind of filter is based on the connection law which can detect the crack in the pulsed image. The detecting system could be used to identify the crack accurate by the above two steps, which would be confirmed by the results. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to detect crack in metals by utilizing the magnetic optical image (MOI) method. MOI detection is one of a nondestructive testing method, which is based on the Faraday magneto-optical effect. The artificial neural network (ANN) approach is applied to identify the crack, according to the dynamically threshold selection. There are two kinds of threshold vectors that are proposed by the ANN algorithm. A good threshold can be obtained from the vectors using a law. The new image acquired is processed by a magnetic domain spots filter. This filtering method is based on the connection law who holds good ability to process the spots in the MOI image. Based on these methods, the detecting system can recognize the crack clearly and the results would confirm it. [ABSTRACT FROM AUTHOR]

This paper investigates how to track a minimum energy consumption in the lighting system despite of environmental variations. A hardware-in-the-loop prototype of an adaptive minimum energy usage for lighting control is developed, designed and built. A modified extremum seeking control algorithm is proposed to minimize energy usage in the lighting system, while a backstepping controller is employed to maintain a desired light level. The hardware-in-the-loop experimental results are given to show the practicality and effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

In this paper, a global peak searching algorithm is proposed for multimodal optimization problem. The proposed algorithm is built through combining gradient-based stochastic extremum seeking method with iterative approach. By increasing the initial search point, the gradient-based stochastic extremum seeking algorithm with different initial condition is iteratively operated to seek a list of the local extreme values near different initial points. Then, the global peak can be found by comparing the list of the local extreme values. The stability anlysis and working process of the global peak searching algorithm is proven. Simulation results are given to show the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of stability analysis for uncertain neutral-type neural networks with Markovian jumping parameters and interval time-varying delays. By separating the delay interval into multiple subintervals, a Lyapunov–Krasovskii methodology is established, which contains triple and quadruple integrals. The time-varying delay is considered to locate into any subintervals, which is different from existing delay-partitioning methods. Based on the proposed delay-partitioning approach, a stability criterion is derived to reduce the conservatism. Numerical examples show the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper offers a novel distributed control scheme for the Cucker-Smale model to examine the leader-follower flocking behavior on networks with both cooperative and competitive interactions among agents. The core idea of the proposed scheme is to characterize the influence of cooperation and competition between agents through positive and negative weight functions with respect to the interaction distance, respectively. Based on the tool of infinite products of super-stochastic matrices, we establish mathematical inequalities about the intensities of cooperation and competition, and further obtain the algebraic conditions that depend on factors such as the initial states of agents, topological structure and weight functions. Moreover, we also discuss the influence of these factors on the least exponential convergence rate and the final position errors among agents. The obtained theoretical results are illustrated through simulation examples. [ABSTRACT FROM AUTHOR]

Abstract: Flexible endoscopic tools are considerably applied in industrial image based inspecting operations, but none of them are currently effective enough to carry out machining tasks, such as grinding. If machining and inspection can be done in a single step, significant amount of labor force, money and energy can be saved in industrial repairing and maintenance tasks. This paper proposed a concept design of novel endoscopic machining tool, which aims at quantitatively and precisely removing material from imperfect components in hard-to-reach cavities, such as turbine blades in a jet engine. Prediction models are built to estimate the pose, force and material removal rate (MRR) of a modified PENTAX ES-3801 endoscope. Preliminary experimental results show that in two-dimensional (2D) grinding configuration the MRR average error of 22% has been achieved for 18 samples tested. In the end, concept designs of self-stabilized endoscopic grinding tool are proposed and discussed. [Copyright &y& Elsevier]

Abstract: This paper describes a power management chip for wireless powering capsule endoscopy, including over-voltage protection circuit RF limiter, CMOS rectifier and low dropout regulator (LDO). Bulk commutation technique is applied to suppress the substrate leakage current problem of CMOS rectifier. A bandgap circuit used as reference for LDO is optimized carefully and has a more than −50dB PSR at 2MHz, which can effectively suppress the ripple of rectifier output used as input voltage of LDO. It incorporates a voltage controlled current source (VCCS) compensation network to make sure the loop’s stability is not dependent on the output capacitor’s Equivalent Series Resistance (ESR). The proposed chip has implemented in 0.35μm CMOS technology and the measurement results show that it can provide as high as 63.8mA output current at a 3V output voltage. The PMC has been used in a wireless powering system designed for capsule endoscope application. Experiment results show that the Power Management Chip (PMC) can deliver as high as 191mW DC energy to the load, imitating the physical condition in a biomedical environment in a human body. [Copyright &y& Elsevier]

• Hybrid uncertainty is represented by probability-box and dempster-shafer Structure. • A dependency bounds analysis method is proposed for non-deterministic dependency problem. • Hybrid uncertainty and non-deterministic dependency are integrated and propagated in bayesian network. • A comparison of the proposed method with the frechet inequalities method and 2-stage monte carlo method is performed. • High narrowing rates during execution time are obtained by the proposed method. In reliability assessment, a difficulty is to handle a complex system with hybrid uncertainty (aleatory and epistemic uncertainty) and dependency problem. Probability-box is a general model to represent hybrid uncertainty. Arithmetic rules on the structure are mostly used between independent random variables. However, in practice, dependency problems are also common in reliability assessment. In addition, in most real applications, there is some prior information on the dependency of components, but the available information may be not enough to determine dependent parameters. The issue is named non-deterministic dependency problem in the paper. Affine arithmetic is hence used to produce dependent interval estimates. The arithmetic sometimes has a better effect than probability-box arithmetic (interval arithmetic) in dealing with dependency problem. Bayesian network is a commonly used model in reliability assessment. Under Bayesian network framework, this paper proposes a dependency bounds analysis method that combines affine arithmetic and probability-box method to handle hybrid uncertainty and non-deterministic dependency. For the sake of illustration, this method is applied to two real systems. To show the advantages of the proposed method, the proposed method is compared with the Frechet inequalities and 2-stage Monte Carlo method in the second case study. [ABSTRACT FROM AUTHOR]

Describes how the semi-supervised transfer component analysis method estimates the battery SOH based on the KRR model. Shows the process of the t semi-supervised transfer component analysis method. • The idea of knowledge transfer is proposed for estimating battery state of health. • A small amount of samples are used to achieve accurate state of health estimation. • Multi-Features indication of battery state of health are extracted. • The correlation between features and targets is measured by mutual information. • The state of health is estimated effectively with less than 2.5% by various errors. Accurate state-of-health estimation can ensure the safe and reliable operation of Lithium-ion batteries in any given application. Nevertheless, most of the state-of-health estimation methods require a large amount of laboratory aging data to offer precise results. As obtaining battery aging data under laboratory conditions requires a considerable amount of time and incurs high economic costs, in this paper, a method based on transfer learning is proposed to monitor state-of-health of batteries. A novel data processing method based on maximum mean discrepancy is considered to eliminate redundant information and minimize the difference between different data distributions. Then, mutual information is used to prove that the correlation between processed data is not decreased. To validate the developed transfer learning method, the data sets of four batteries in different working conditions are considered. Different error-detection methods, maximum average error, mean squared error and root mean squared error, which are utilized to evaluate the proposed model. The state of health is estimated effectively with less than 2.5 % error considering the aforementioned errors after processed by using semi-supervised transfer component analysis algorithm, although the training set only accounts for about 35% of the entire set. The results indicate that transfer learning plays an important role in improving the estimation accuracy of a battery state-of-health. [ABSTRACT FROM AUTHOR]

Passive micro direct methanol fuel cell (μDMFC) which operates based on fuel diffusion is preferred for portable applications for its structural simplicity. In this work, we have systematically investigated multiple variables including the hot-press conditions, current collector channel patterns, current collector open ratios, and their effects on the performance for passive μDMFC by experiments and simulations. Results indicate that vertical stripe pattern (VSP) is preferred for both anodes and cathodes due to the upward reaction products drift by natural convection. Open ratio of 45.6% and 35.8% are found to yield the best performance for anode and cathode, respectively. In addition, the external environmental conditions of vibration frequency, cell orientation, environmental temperature and atmospheric pressure are all discussed in detail in this work. The optimized fabrication, assembly and operation parameters shed light on the design considerations necessary for the wide adaptation of high-performance and durable passive μDMFC for portable applications. • Hot-pressing parameters of pressure, time and temperature are optimized. • A 3D model considering contact resistance is established. • The current collectors with different channel patterns are evaluated. • The current collectors with different open ratios are optimized. • The effects of external environmental parameters are evaluated. [ABSTRACT FROM AUTHOR]

Highlights • The containment control issue for discrete-time second-order multi-agents (MASs) with asynchronous intermittent communication is examined in this paper. • Hybrid tools including matrix theory and the composite binary relation are utilized to analyze this problem. • It is proved that although the followers can gradually enter into the convex hull of the leaders, and their positions after entering the convex hull may be time-varying. Abstract In this paper, a containment control issue for discrete-time second-order multi-agents (MASs) with asynchronous intermittent communication is analyzed, where each agent communicates with some of its neighbors at certain discrete time according to its own clock rather than the complete discrete process and all agents' clocks are independent of each other. By constructing the spanning subgraph of communication topology at each discrete time, the stability analysis of containment control under the asynchronous intermittent communication is equivalently transformed into the products convergence of nonnegative matrices. Hybrid tools including matrix theory and the composite binary relation are utilized to analyze this convergence issue. Unlike the existing results on the containment control with fixed topology, in which the followers will gradually enter into the convex hull constructed by the leaders and their final positions are fixed, it is theoretically proved in this paper that although the followers will enter into the convex hull of the leaders under the asynchronous intermittent communication, their positions after entering the convex hull may always be time-varying. Finally, the theoretical finding is verified by a simulation example. [ABSTRACT FROM AUTHOR]

Highlights • The asynchronous bipartite consensus for a group of agents with second-order dynamics is examined in this paper. • The properties of the product of infinite time-varying row-stochastic matrices from a noncompact set are explored to analyze this problem. • A sufficient condition that depends on switching topologies is established. Abstract The asynchronous bipartite consensus for a group of agents with second-order dynamics is examined in this paper, where the asynchrony means that the time instants when each agent receives the neighbors’ data information are completely independent of other agents’. The communication among the agents is described by a time-varying signed and structurally balanced digraph, which is equivalent to assuming that the agents can be divided into two groups without any common agents, in which the agents within the same group are cooperative and the agents between different groups are competitive. An asynchronous distributed control protocol is designed to implement the bipartite consensus. By using the product properties of row-stochastic matrices from a noncompact set, a sufficient condition can be established under a loose assumption that is the union of communication topologies related to any time intervals with given length has a spanning tree. Finally, a simulation instance is provided to verify the reachability of asynchronous bipartite consensus. [ABSTRACT FROM AUTHOR]

This paper reports on a novel design and fabrication strategy to develop a hybrid porous silicon (PSi)-polyimide-based neural interface probe. The PSi is soluble in the tissue matrix, leaving the flexible polyimide shank inside the tissue as a permanent probe-implant. The flexibility of the PSi-dissolved polyimide shank is possible to reduce the tissue response, resulting from the probe-implant. In-vitro degradation experiment was conducted in phosphate buffer solution (PBS), pH 7.4, at 37 °C. The PSi with over 50% porosity was dissolved in less than 6 days. The electrode contacts were made of Au or Pt; impedance measurements gave values of 6.83 MΩ and 656 kΩ @1 kHz, respectively. The minimum critical bucking force among the fabricated probes was tested to be 71 mN, corresponding to the highest porosities of 70% and 5 mm shank length. Assessment of the cell viability was done using mouse fibroblast cell line, indicating that there was no sign of obvious cell lysis and reduction of cell growth on the device surface. Lastly, the functionality of the probe was proved by successful implantation in rat cortex. The local field potential action spikes were recorded with ±40 μV peak and signal to noise ratio of 7.8. [ABSTRACT FROM AUTHOR]

A bipolar passive direct methanol fuel cell (DMFC) stack for portable applications is designed, fabricated and tested. Stainless steel sheet is chosen to fabricate the current collectors by using the traditional wire cutting and laser beam cutting techniques. A 3.5 μm Au layer is deposited on the current collectors using electroplating method to prevent electrochemical corrosion. A novel design of the current collectors is proposed, which makes internal and external electrical connections be seamlessly integrated so that the resistance loss can be reduced. The maximum power density of the passive stack is 18.7 mW cm −2 at 3 M methanol concentration. The effect of the passive DMFC stack placement mode is studied. The results indicate that the passive DMFC stack in mode B (vertical cathode air channels) exhibits better and more stable performance than its counterpart in mode A (parallel cathode air channels) in discharging of high currents. Finally, the bipolar passive DMFC stack proves its good performance in powering the experimental fan in 100 days while performance deterioration behaviour is also detected. [ABSTRACT FROM AUTHOR]

In recent years, the energy problem has been a universal concern. In order to improve the lighting energy efficiency and reduce the electric energy consumption, this paper develops an energy-saving control strategy for the lighting system with multiple lighting sources. The control strategy presented in this paper includes two parts: a new multivariate extremum seeking control method with Newton algorithm is developed to minimize the light-energy consumption by separately manipulating the brightness of multiple lighting sources, and a proportion-integration-differentiation control approach is adopted to realize the desired lighting level. The proposed scheme can increase the convergence speed of the closed loop system toward the minimum light-energy consumption, meanwhile, the accuracy of the control strategy will be improved. Experimental results illustrate that the light-energy consumption via the proposed method can reach more rapidly to a smaller vicinity of the minimum energy point, so, the lighting energy efficiency is greatly increased accordingly. [ABSTRACT FROM AUTHOR]

In this paper, a fractional-order sliding mode controller (FO SMC) based on an FO exponential switching technique and an FO proportional–integral (PI) switching surface is proposed for robust stabilization of uncertain FO nonlinear systems. The FO exponential switching technique, involving an FO sign function, is designed to guarantee the existence of the sliding motion in finite time. Reaching time is analytically derived and the reachability analysis is presented to explicate the superiority of the control performance. The stability analysis of sliding mode dynamics is performed relying on stable region analysis of FO systems. Simulation and practical results demonstrate the advantages of the designed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates robust stability for fractional-order (FO) singular nonlinear systems. The FO system is disturbed by external uncertainty and disturbance. A central analysis technique is enabled by proposing a fundamental boundedness lemma, for the first time. This lemma is used for robust stability analysis of FO systems, especially for Mittag–Leffler stability analysis of FO nonlinear systems. More importantly, how to obtain a more accurate bound is given to reduce conservative. An FO proportional-derivative (PD) controller is proposed to normalize the FO singular system. Furthermore, a criterion for stability of the normalized FO nonlinear systems is provided by linear matrix inequalities (LMIs). Finally, two illustrative simulation examples are presented to illustrate effectiveness of the proposed stability notion. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports fast crack profile reconstruction methods using transient slices and spectral components of pulsed eddy current (PEC) signals after a review of the state-of-the-art and current challenges. These methods provide initial approximate profiles for crack shape reconstruction, and have potential to reduce the computing time. Experimental samples, results, and reconstructions have been presented and discussed. Comparative studies of different profile reconstructions using different PEC signals such as amplitude, phase, real and imaginary values of spectral components, transient slices, have also been conducted using reconstruction Mean Square Errors (MSE). The results show that the profiles estimation using the imaginary values of spectral components is more stable and accurate than the others. [Copyright &y& Elsevier]

• Possible CCF scenarios are modeled and quantified by decomposed partial α factors. • Uncertainties for CCF events are reduced by hierarchical Bayesian inference method. • Reliability of redundant uncertain system with CCFs is modeled by survival signature. • Importance of components and CCF events are defined and ranked. • The proposed method is effectively used to analyze the reliability of a satellite subsystem. Redundant design has become the commonly used technique for ensuring the reliability of complex systems, which calls for great concern to common cause failure problems in such systems. Incomplete data in combination with vague judgments from experts introduce imprecision and epistemic uncertainties in the performance characterization of components. These issues need to be taken into account for assessing the system reliability. In this paper, a comprehensive reliability assessment method is presented by adopting the concept of survival signature to estimate the reliability of complex systems with multiple types of components. Particular attention is devoted to common cause failures (CCFs), which are modeled and quantified by decomposed partial α-decomposition method. Uncertainties caused by incomplete data for CCF events are reduced by hierarchical Bayesian inference. The component importance measure is enhanced to assess the importance of various possible CCF scenarios and to identify their potential impact on system reliability. The presented method is used to analyze the reliability of a dual-axis pointing mechanism for communication satellite, which is a commonly used satellite antenna control mechanism. The engineering application demonstrates the effectiveness of the method. [ABSTRACT FROM AUTHOR]