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This article is concerned with the secure state estimation problem of a linear discrete-time Gaussian system in the presence of sparse integrity attacks. $\mathbf {m}$ sensors are deployed to monitor the state and $\mathbf {p}$ of them can potentially be compromised by an adversary, whose data can be arbitrarily manipulated by the attacker. We show that the optimal Kalman estimate can be decomposed as a weighted sum of local state estimates. Based on these local estimates, we propose a convex optimization based approach to generate a more secure state estimate. It is proved that our proposed estimator coincides with the Kalman estimator with a certain probability when all sensors are benign. Besides, we establish a sufficient condition under which the proposed estimator is stable against the $\mathbf {(p,m)}$ -sparse attack. A numerical example is provided to validate the secure state estimation scheme.

This paper proposes a novel and applicable approach to calculate the reactive power loss of converter transformer under dc bias. By using this proposed method, only general information of the converter transformer and the network is needed for the calculation within a certain dc current range. Specifically, a three-dimensional model of $\pm$ 800 kV converter transformer model for simulation test is established by the finite element method. Through simulation test, the electromagnetic characteristics and reactive loss characteristics of converter transformer under dc bias can be obtained, and the relationship between the bias current and the reactive loss of $\pm$ 800 kV converter transformer is quantified. Simulation results validate the feasibility of proposed algorithm.

The increasing emissions from the transportation sector pose substantial hazards to the environment and human health around the world. With the rapid development of information and communication technologies, ridesplitting, a form of ridesourcing service accessed via smartphone applications, enables passengers with similar origins and destinations to be matched to the same driver and share the ride. This is regarded as a promising travel mode that could mitigate air pollution. However, because of a lack of quantitative analysis, the environmental benefits of ridesplitting have not been rigorously justified. As vast amounts of observed data of ridesourcing have become increasingly available, this study quantifies the environmental benefits of ridesplitting based on the global positioning system (GPS) trajectory and trip order datasets of DiDi Chuxing in Chengdu, China. First, the saved distances of ridesplitting are calculated by analyzing the travel distances of both ridesplitting trips and the corresponding trips under non-ridesplitting conditions. Then, the emission factors of CO, NOx, and HC are estimated by a localized MOVES model. Combining the saved distances and emission factors, the emission reductions from each ridesplitting trip can be calculated. The results show that ridesplitting can decrease the travel distance by 22% on average compared with non-ridesplitting. As a consequence, the average emission reductions per ridesplitting trip are 10.601 g of CO, 0.691 g of NOx, and 1.424 g of HC, respectively. This study provides a better understanding of the environmental benefits of ridesplitting and theoretical guidance for the government’s decision-making in green transport planning.

High-volumetric-energy-density lithium-ion batteries require anode material with a suitable redox potential, a small surface area, and facile kinetics at both single-particle and electrode level. Here a family of coarse-grained molybdenum substituted titanium niobium oxides Mo[subscript x]Ti[subscript 1−x]Nb[subscript 2]O[subscript 7+y] (single crystals with 1~2 μm size) underwent hydrogen reduction treatment to improve electronic conduction was synthesized, which is able to stably deliver a capacity of 158.5 mAh g[superscript −1] at 6,000 mA g[superscript −1] (65.2 % retention with respect to its capacity at 100 mA g[superscript −1] ) and 175 mAh g[superscript −1] (73 % capacity retention over 500 cycles) at 2,000 mA g[superscript −1], respectively. Via careful in situ electrochemical characterizations, we identified the kinetic bottleneck that limits their high-rate applications to be mainly ohmic loss at the electrode level (which mostly concerns electron transport in the composite electrodes) rather than non-ohmic loss (which mostly concerns Li+ lattice diffusion within individual particles). Such a kinetic problem was efficiently relieved by simple treatments of Mo substitution and gas-phase reduction, which enable full cells with high electrode density, and high volumetric energy/power densities. Our work highlights the importance of diagnosis, so that modifications could be made specifically to improve full-cell performance.

International audience; Poly(D,L-lactide-co-glycolide)-poly(ethylene glycol) (PLGA-PEG) diblock copolymers with different compositions were synthesized by ring-opening polymerization of D,L-lactide and glycolide, using monomethoxy PEG as macro-initiator. The resulting copolymers were characterized by nuclear magnetic resonance, gel permeation chromatography, and critical micelle concentration analyses. Self-assembly of the copolymers yielded aggregates of different architectures, including spherical micelles and a mixture of spherical and worm-like micelles with Y-junctions. The self-assembled architecture depends on both the hydrophilic/hydrophobic balance and the molar mass of copolymers. Valsartan, a widely used drug in the treatment of hypertension, was loaded in micelles using a co-solvent evaporation method. High drug-loading content was obtained for worm-like micelles. in vitro drug release was performed at 37°C in pH 7.4 phosphate-buffered saline. An initial burst release is detected in all cases, followed by slower release up to 9 days. The overall release rate is strongly dependent on the degradation of micelles. Copolymers with short PLGA blocks exhibit faster drug release due to faster degradation of micelles, and worm-like micelles present slower drug release as compared to spherical ones. Therefore, PLGA-PEG copolymer micelles with high drug-loading capacity, different architectures, and variable drug release rates could be most attractive for sustained delivery of valsartan.

This paper is concerned with the problem of designing a control strategy to guarantee stability in probability for high-order stochastic systems. The control hinges on the sliding-mode scheme. We first prove that the control design can stabilize a fast terminal sliding-mode function. We further show that the stable sliding mode is able to assure the stability in probability for the high-order stochastic system. The resulting system may account nonvanishing diffusion terms, which is regarded as a novelty. The derived control strategy has implications for applications—experiments are carried out to control the pitch angle of a one-degree-of-freedom aerial device. The corresponding experimental results demonstrate the benefits and effectiveness of our approach.

This article addresses the dissipativity-based asynchronous repetitive control problem for networked Markovian jump systems subject to time delays and partly accessible mode detection probabilities. A hidden Markov model is introduced to describe the asynchronous phenomenon between the system modes and controller modes. Based on this, an asynchronous repetitive controller is proposed. By utilizing the lifting technique, the 1-D delayed Markovian jump system and controller governing equations are converted into a stochastic and closed-loop 2-D delayed model to describe the control and learning actions. Utilizing a stochastic Lyapunov functional, sufficient conditions in terms of matrix inequalities are derived such that the closed-loop system is mean-square stable and achieves the specified $(\mathscr {W}_1,\mathscr {W}_2,\mathscr {W}_3)$ - $\gamma$ -dissipative performance. Under the assumption that the input matrix is full column rank in all modes of operation, a set of feasible sufficient conditions described by linear matrix inequalities is established by making use of the Schur complement. A procedure for synthesizing the controller parameters is also provided. A detailed numerical example with simulation results is presented to validate the proposed dissipativity-based asynchronous repetitive control design scheme.

This paper considers the problem of asynchronous ${H}_{{\infty }}$ control for networked Markovian jump systems subject to probabilistic packet dropouts and communication delays in the measurement channel. A new dynamic output-feedback-based asynchronous controller is proposed wherein the dynamic output-feedback controller modes need not synchronize with the system modes. By utilizing results from stochastic Lyapunov–Krasovskii stability theory, sufficient conditions in terms of matrix inequalities are derived such that the closed-loop networked Markovian jump system is stochastically stable and achieves the prescribed ${H}_{{\infty }}$ performance. Using the Schur complement technique and under the assumption that the input matrix is full rank, the sufficient condition is reduced to a linear matrix inequality and the dynamic output-feedback-based asynchronous controller is synthesized. A detailed numerical example with simulation results are presented to evaluate the proposed controller design scheme.

The design of irregular subarrayed planar phased arrays composed of modular tiles is a research area of increasing interest. In this article, a heuristic iterative convex relaxation programming (H-ICRP) framework is proposed. By formulating the tiling of irregular subarray as a binary programming problem, this framework is suitable for arbitrary array aperture and subarray structure. To achieve exact aperture cover, the nonconvex binary constraint is relaxed to a convex approximation and solved through multiple iterations. Furthermore, for better performance of the scanning radiation pattern, the multitask Bayesian compressive sensing (MT-BCS) solver is adopted to find a heuristic initial iteration point instead of randomizing, such that the robustness and effectiveness can be improved remarkably. Good performance and potentialities of the proposed method are verified by comparing with existing approaches in various numerical examples.

In this letter, a general framework of cognitive resource allocation for target tracking in radar networks is proposed. Firstly, an allocation strategy evaluation metric is established in this framework, i.e., the predicted conditional Cramer-Rao lower bound (PC-CRLB), for evaluating the future response of each candidate allocation strategy. Then, the optimal resource allocation strategy can be found by solving a constrained optimization problem. To specify the framework implementation details, a dwell time allocation problem is considered. For this given problem, the analytical expressions of PC-CRLB and its derived scalar strategy evaluation metric are derived, enabling us to convert the allocation problem to a second-order cone program (SOCP). Numerical results demonstrate the effectiveness of the proposed framework.

Thermal decomposition of cyclohexane at temperatures up to 1310 K was performed using flash pyrolysis coupled with vacuum ultraviolet (118.2 nm) photoionization time-of-flight mass spectrometry. The experimental results revealed that the major initiation reaction of cyclohexane decomposition was C–C bond fission leading to the formation of 1,6-hexyl diradical. The 1,6-hexyl diradical could isomerize to 1-hexene and decompose into ˙C3H7 + ˙C3H5 and ˙C4H7 + ˙C2H5. The 1,6-hexyl diradical could also undergo direct dissociation; the C4H8 fragment via the 1,4-butyl diradical intermediate was observed, serving as evidence of the 1,6-hexyl diradical mechanism. Quantum chemistry calculations at UCCSD(T)/cc-pVDZ level of theory on the initial reaction pathways of cyclohexane were performed and found to be consistent with the experimental conclusions. Cyclohexyl radical was not observed as an initial intermediate in the pyrolysis. Benzene was produced from sequential H2 eliminations of cyclohexane at high temperatures.

This paper provides a periodic event-based asynchronous H ∞ filter design for switched systems subject to limited communication resources. The governing equations for the physical system are combined with those of the proposed event-based asynchronous filter and the resulting equations are formulated as a switched filtering error system with time-varying delay. For the achieved switched delay filtering error system, sufficient conditions in terms of linear matrix inequalities are obtained to achieve exponential stability and a prescribed H ∞ disturbance attenuation level. Tools and techniques from delay-dependent Lyapunov theory, free-weighting matrices, and average dwell time for switched systems are used to obtain the main results. Further, a synthesis procedure for the filter gains, the event-triggering condition parameters, and a lower bound on the average dwell time of the switching signal is provided. A numerical example on a switched RLC circuit is finally provided to evaluate the proposed design and results.

This paper develops an asynchronous mode-dependent repetitive control strategy with periodic event-based dynamic output feedback for periodic trajectory tracking of continuous-time switched systems subject to time-varying switching delays between system modes and controllers and limited communication capacity in the feedback channel. By employing the input delay approach, the overall system is modelled as an augmented closed-loop switched system with both constant and time-varying state delays. A co-design framework is proposed for simultaneously designing the controller, event-triggering mechanism and mode switching signal. Under the co-design framework, using piecewise Lyapunov functional, free-weighting matrices and average dwell time technique, sufficient conditions are derived for ensuring the augmented closed-loop system to be exponentially stable with a prescribed $H_{\infty }$ attenuation level $\gamma $ for an exogenous disturbance input. The performance of the proposed controller design scheme is verified via numerical simulation results on a switched RLC series circuit system.

Coherently combining dual identical radars is a promising technology that can obtain a 23 times signal-to-noise ratio promotion over a single radar. The basic principle of dual-radar coherently combining is to adjust transmitting/receiving time and phase of each radar via the coherent parameters (CPs), with the purpose of achieving coherent-on-transmit and -receive. However, this technology has not been researched systematically, especially in the target moving scenario. In this paper, a signal processing paradigm for dual-radar coherent combination is proposed. Two stages exist in the proposed paradigm: coherence preparation stage and coherence maintenance stage. The former stage is considered as a means of bootstrapping to the latter stage, by offering the necessary coherent combining information (predicted transmit CPs and estimated synchronisation errors). And a great coherent gain is obtained in the latter stage, which allows dual-radar works in a fully coherent transmit and receive mode. In both stages, CPs estimation and prediction are the indispensable key steps, whose corresponding algorithms and constraints are developed, respectively. Given to this proposed paradigm, a dual-radar coherently combining example is implemented under a ballistic target tracking scenario, whose results verify the effectiveness of the proposed paradigm.

The paper presents a method for checking the robust mean square stability of continuous-time Markov jump linear systems. The robustness arises in the analysis due to the assumption that the Markovian transition probability matrix is partially known. The corresponding infinite-dimensional robust stability problem, difficult to solve, is then converted into a probabilistic problem, amenable to the numerical viewpoint, taking advantage of the randomized (scenario) approach. The paper shows examples—including a real-time electronic-circuit application—for which the results from the literature fail to determine the robust stability but the randomized approach gives a positive answer.

Subarray design technique is widely employed in the design of planar phased arrays. However, it is hard to obtain full coverage and good radiation performance with the given shape of subarrays and array aperture. In this letter, the subarray design problem is formulated as an iterative convex relaxation model and solved using some steps subtly. Besides, the scanning sidelobe level is adopted to retrieve the optimal configuration among the found solutions. Numerical experiments are carried out to assess the performance of the proposed method as well as the inherent superiority in adaptive beamforming.

Mechanism of the initial reactions of chlorine trifluoride oxide (ClF3O) and aluminum based composite fuel was investigated using density functional theory (DFT) at B3PW91/6–311++G (d,p) level and experimental methods. The composite fuel mainly contained isopropyl nitrate (IPN), hexogen (RDX), ammonium perchlorate (AP), n-decane, paraffin and aluminum powder. The results showed that ClF3O reacted exothermically with IPN, RDX, and hydrocarbons (n-decane and paraffin) via electrophilic substitution. The equatorial F atom was the reactive site of ClF3O. The reactive sites of IPN, RDX and hydrocarbon were different C H bonds according to the results of dual descriptor index. Reactivity of the composite fuel components was in the sequence of n-decane ≈ paraffin > RDX > IPN » AP according to the energy barriers. The value of released energy from the reaction of ClF3O with n-decane was greater than 400 kJ/mol, resulting in thermal decomposition of the composite fuel. The results from XPS indicated that the composite fuel was wrapped by hydrocarbons. ClF3O reacted with hydrocarbon first and then initialized the combustion of the composite fuel in the presence of oxygen. The emission spectrum of the composite fuel combustion was studied using an intensified CCD camera. Five characteristic radical intermediates (CH, C2, OH, NO and AlO) were determined.

We propose to enhance the performance of localized plasmon structured illumination microscopy (LP-SIM) via intensity correlations. LP-SIM uses sub-wavelength illumination patterns to encode high spatial frequency information. It can enhance the resolution up to three-fold before gaps in the optical transfer function (OTF) support arise. For blinking fluorophores or for quantum antibunching, an intensity correlation analysis induces higher harmonics of the illumination pattern and enlarges the effective OTF. This enables ultrahigh resolutions without gaps in the OTF support, and thus a fully deterministic imaging scheme. We present simulations that include shot and external noise and demonstrate the resolution power under realistic photon budgets. The technique has potential in light microscopy where low-intensity illumination is paramount while aiming for high spatial but moderate temporal resolutions.

This paper investigated the sliding mode load frequency control (LFC) for an multi-area power system (MPS) under deception attacks (DA). A Luenberger observer is designed to obtain the state estimate of MPS. By using the Lyapunov-Krasovskii method, a sliding mode surface (SMS) is designed to ensure the stability. Then the accessibility analysis ensures that the trajectory of the MPS can reach the specified SMS. Finally, the serviceability of the method is explained by providing a case study.

Since the subsidies of solar energy photovoltaic power may be eliminated in the short run, it is inappropriate to neglect the cost of photovoltaic power in economic dispatch of thermal-photovoltaic power system. In this day-ahead economical schedule of photovoltaic-thermal power units, the cost of photovoltaic (PV) power generation be added in objective function. In such a way, a new objective function of economic dispatch is constructed to be compatible with two parts, i.e., thermal power units expense and PV cost. Power balance of this system, the rotate reserve, the output power range, the open and close time of thermal power units, etc. are taken as the constraints of economic dispatch. Unit commitment (UC) problem can use the genetic algorithm (GA) based on real matrix coding be solved. Finally, two study cases are conducted to verify that the total cost can be reduced by reasonable utilization of PV generation.

This paper investigates the rotor angular velocity state estimation of permanent magnet linear synchronous motor (PMLSM) sensorless system. The velocity feedback is an indispensable link to realize the accurate speed control of PMLSM. Accurate rotor information acquisition is the essential problem of the whole control system, since it is impossible to obtain rotor information by traditional mechanical sensors in the non-position sensor control of PMLSM drive system. To work out this problem, this paper raises a non-position sensor control method based on unscented particle filter (UPF). Firstly, the nonlinear dynamic model is established for PMLSM. In the framework of particle filter (PF), the latest measurement information is to generate the predicted particles. Finally, a numerical example and simulated results show that UPF can accurately estimate the rotor angular velocity.

High-voltage direct current (HVDC) is increasingly utilized for long-distance electric power transmission, mainly due to its low resistive losses. In this paper, a decentralized control strategy is proposed to address the secondary frequency restoration and real power sharing problem for multi-terminal direct current (MTDC) transmission systems. We establish a sufficient stability condition to guarantee that the designed decentralized leaky integral controller can restore the frequency to its nominal value. Furthermore, the proposed controller can adjust the real power sharing ratio according to different working conditions. An MTDC system consisting of 4 AC systems is built in MATLAB Simulink environment. Numerical simulations are conducted to validate the effectiveness of proposed decentralized control approach.

This paper investigates the quasi-synchronization problem of the stochastic heterogeneous complex dynamical networks with impulsive couplings and multiple time-varying delays. It is shown that this kind of dynamical networks can achieve exponential quasi-synchronization by exerting impulsive control added on only one chosen pinning node. By employing the Lyapunov stability theory, some sufficient criteria on quasi-synchronization for this dynamical network are established, revealing the relationship between the quasi-synchronization performance and the stochastic perturbations as well as the frequency and strength of impulsive coupling. Finally, some numerical examples are used to illustrate the effectiveness of the main results.

All-optical thermometry presents a promising avenue of investigation for sensitive biological and electronic systems, with methods free of radio-frequency interference of particular importance. In this work, an all-optical scanning fiber thermometer is tested and shown to possess $5\phantom{\rule{0.2em}{0ex}}\ensuremath{\mu}\mathrm{m}$ spatial and $20\phantom{\rule{0.2em}{0ex}}\mathrm{mK}/\sqrt{\mathrm{Hz}}$ temperature resolution. This probe is then used to generate noncontact scanning thermal images of active circuit elements with microscale thermal features.

In this paper, a novel multiobjective lightning flash algorithm (MOLFA) is proposed to solve the multiobjective optimization problem. The charge population state of the lightning flash algorithm is defined, and we prove that the charge population state sequence is a Markov chain. Since the convergence analysis of MOLFA is to investigate whether a Pareto optimal solution can be reached when the optimal charge population state is obtained, the development of a charge population state is analyzed to achieve the goal of this paper. Based on the martingale theory, the MOLFA convergence analysis is carried out in terms of the supermartingale convergence theorem, which shows that the MOLFA can reach the global optimum with probability one. Finally, the effectiveness of the proposed MOLFA is verified by a numerical simulation example. National Research Foundation (NRF) Published version This work was supported in part by the National Key R&D Program of China (Grant no. 2016YFB0900600), National Natural Science Foundation of China (Grant nos. 51877174 and 61903296), State Key Laboratory of Advanced Electromagnetic Engineering and Technology (Huazhong University of Science and Technology) (Grant no. AEET2018KF001), State Key Laboratory of Electrical Insulation and Power Equipment (Xi’an Jiaotong University) (Grant no. EIPE18201), and High Level Talents Plan of Shaanxi Province for Young Professionals, and partially supported by National Research Foundation (NRF), Singapore, under Future Resilient Systems Programme-Stage II.

We consider the quasi-synchronization problem of a continuous time generalized Markovian switching heterogeneous network with time-varying connectivity, using pinned nodes that are event-triggered to reduce the frequency of controller updates and internode communications. We propose a pinning strategy algorithm to determine how many and which nodes should be pinned in the network. Based on the assumption that a network has limited control efficiency, we derive a criterion for stability, which relates the pinning feedback gains, the coupling strength, and the inner coupling matrix. By utilizing the stochastic Lyapunov stability analysis, we obtain sufficient conditions for exponential quasi-synchronization under our stochastic event-triggering mechanism, and a bound for the quasi-synchronization error. Numerical simulations are conducted to verify the effectiveness of the proposed control strategy. Accepted version

This paper investigates the problem of asynchronous repetitive control for a class of discrete-time Markovian switching systems. The control goal is to track a given periodic reference without steady-state error. To achieve this goal, an asynchronous repetitive controller that renders the overall closed-loop switched system mean square stable is proposed. To reflect realistic scenarios, the proposed approach does not assume that the system modes are available synchronously to the controller but instead designs a detector that provides estimated values of the system modes to the controller. Based on a detected-mode-dependent estimator, the plant and asynchronous repetitive controller are formulated as a closed-loop stochastic system. By utilizing tools from stochastic Lyapunov–Krasovskii stability theory, we develop sufficient conditions in terms of linear matrix inequalities (LMIs) such that the closed-loop system is mean square stable and also simultaneously establish a synthesis procedure for obtaining the gain matrices. We provide numerical simulations on an electrical circuit switched system to illustrate the approach.

This paper presents a strategy for computing model predictive control of linear Gaussian noise systems with probability constraints. As usual, constraints are taken on the system state and control input. The novelty relies on setting bounds on the underlying cumulative probability distribution, and showing that the model predictive control can be computed in an efficient manner through these novel bounds— an application confirms this assertion. Indeed real-time experiments were carried out to control a direct current (DC) motor. The corresponding data show the effectiveness and usefulness of the approach.

This paper considers the periodic reference tracking problem for continuous-time semi-Markovian jump systems. An observer-based robust H∞ modified repetitive controller with logarithmically quantis...

Here, we report on the effect of different antisolvent dripping on film morphology and charge recombination of mixed formamidinium–methylammonium tin iodide (FA0.75MA0.25SnI3) as a light absorber in perovskite solar cells. N,N-dimethyl methanamide (DMF) and dimethyl sulfoxide (DMSO) were used as the mixed solvent in the perovskite precursors together with tin fluoride (SnF2) as an additive. Diethyl ether (DE), toluene (TL), and chlorobenzene (CB) were employed as antisolvents for comparison. Our results show that CB as an antisolvent leads to a dense and uniform Sn-based perovskite film. The maximum power conversion efficiency of our Sn-based perovskite solar cell achieves 9.06% (9.02%) under forward (reverse) voltage scan under AM 1.5G 100 mW/cm2 illumination. The encapsulated cells show good long-term stability with ∼75% of their initial efficiency retained over a period of 30 days of storage. Our work suggests the promising potential to further improve the performance of Pb-free Sn-based perovskite sol...

Frequency diverse array (FDA) can offer new degrees-of-freedom, but the target localization of basic FDA is fundamentally limited by the range-angle-coupled and range-periodic peaks of beampattern. In this paper, we propose a localization system with the combination of subarray-based FDA and full-band FDA, as the transmitter and the receiver, respectively. The transmit and receive beampatterns are both decoupled in range and angle domains. Target range-angle localization is achieved by two steps. First, using the outputs of subarrays, we solve the range ambiguity and obtain a coarse location. Second, the monopulse processing of range-angle localization is developed for the proposed system by taking the coarse location as the receiving beam pointing. The localization performance is also analyzed in Cramer-Rao lower bound, computational complexity, and output signal to interference-plus-noise ratio. Several simulation results demonstrate that unambiguous target range-angle localization can be achieved with a low computational cost by the proposed method.

Distributed radars have the potential to combine coherently for achieving a high signal-to-noise ratio (SNR) while maintaining a moderate antenna size. The key to coherently combining multiple radars is obtaining accurate coherent parameters (CPs), which are used to adjust the transmitting/receiving time and phase of each radar. One approach for CP estimation is to transmit orthogonal waveforms. However, ideally, orthogonal waveforms occupying the same frequency band may not be found in practice. Cross-correlation energy leakage exists between non-orthogonal waveforms, which seriously impairs the accurate acquisition of CPs. To solve this problem, we propose a clean signal reconstruction approach for CP estimation. This approach reconstructs clean echoes by gradually stripping out the cross-correlation energy leakage with a reconstruction-elimination-reconstruction framework. And CPs are obtained from these reconstructed clean echoes. Since the majority of cross-correction energy leakages are eliminated, enhanced CP estimation performance can be achieved. Verified simulations are designed for a dual radar scenario. Results show that the proposed approach significantly improves the performance of CP estimation while reducing the SNR requirement for coherently combining multiple radars.

The mechanism of the reactions of ClF3O and n-decane had two stages. The first stage was the initial reaction between ClF3O and n-decane. The initial reactions were investigated using a density functional theory (DFT) method. The results showed that the critical part of the mechanism of the initial reaction was the roaming of the HF intermediate. A H atom on n-decane was abstracted by a F atom on ClF3O to produce HF. The formed HF roamed around and then broke to give ClFO, fluorinated decane and a new HF molecule. The initial reactions were considered to be barrier-less reactions and extremely exothermic. The average released energy of the initial reactions was 412.9 kJ mol−1, which was great enough to cause thermal decomposition of n-decane. The second stage included the reaction between ClFO and n-decane and the thermal decomposition of n-decane. The secondary reactions involving ClFO were also studied using a DFT method. ClFO was less reactive than ClF3O. The average energy barrier of the reactions of ClFO and n-decane was 116.3 kJ mol−1 and the average released energy was 266.5 kJ mol−1. Thermal decomposition of n-decane was evidenced by the emission spectra of the characteristic radical intermediates CH and C2, which were observed using an intensified charge-coupled device (ICCD) system. The main gaseous products of the thermal decomposition of n-decane, as identified using gas chromatography, were hydrogen, ethylene and acetylene. The experimental results showed that the thermal decomposition of n-decane was an important secondary reaction following the initial reactions.

A novel glycidyl resin 2,7-bis(β-epoxypropylthio)thianthrene (4SEP) with high refractive index was synthesized and characterized by 1H NMR, FT IR and FD-MS analyses. The kinetics of 4SEP cured with...

This paper presents a stabilizing control for two-dimensional stochastic differential equations. The stability concept in this study is the stability in probability. To ensure such a stability, the control is designed based on the sliding mode technique, and applied to account stochastic systems. This finding has a practical implication—the proposed control can be used to stabilize a real-time automotive electronic throttle valve. The proposed approach is verified by data collected from experiments.

We consider the problem of estimating the state of a linear time-invariant Gaussian system in the presence of sparse integrity attacks. The attacker can control p out of m sensors and arbitrarily change the measurements. Under mild assumptions, we can decompose the optimal Kalman estimate as a weighted sum of local state estimates, each of which is derived using only the measurements from a single sensor. Furthermore, we propose a convex optimization based approach, instead of the weighted sum approach, to combine the local estimate into a more secure state estimate. It is shown that our proposed estimator coincides with the Kalman estimator with certain probability when all sensors are benign, and we provide a sufficient condition under which the estimator is stable against the (p, m)-sparse attack when p sensors are compromised. A numerical example is provided to illustrate the performance of the proposed state estimation scheme. Published version

Organic Rankine cycle (ORC) is effective for heat-work conversion. However, the system performance should be improved due to the high irreversible loss. The pinch point temperature difference (PPTD) is a very important parameter for the ORC-based plant and is often fixed to be a constant value, especially for low- and medium-grade heat sources. In this paper, the influence of the PPTD on the system performance was analyzed base on the laws of thermodynamics. The net power output, the product of the total thermal conductance, the size parameter (SP), and the volumetric flow ratio (VFR), were calculated. The results show that the net power output and the total thermal conductance are opposite with the PPTD. The optimal PPTD is closely correlated with the heat source inlet temperature (HSIT), and there is a quadratic function between them, with the optimal PPTD from 2 to 21 °C for the HSIT ranging from 80 to 180 °C, which can be popularized in engineering applications.

The nozzle opening pressure of fuel injection systems affects the initial fuel atomization, the fuel injection quantity, the emission characteristics and the operation stability of diesel engines. This paper presents an investigation on the dynamic characteristics of the nozzle opening pressure for a double-solenoid-valve fuel injection system. A numerical model for the nozzle opening pressure based on the fluid–structure interaction theory is established, including the models for the physical properties of the fuel, the leakage rate of the piston pair and the elastic deformation of the piston chamber and the piston pair. Also, experiments were carried out to validate the proposed model. Good agreement was found between the simulated results and the measured results. Based on this model, the effects of some factors on the nozzle opening pressure are analysed. The results show that the rotational speed of the cam, the initial clearance of the piston pair and the sealing length of the piston pair have slight effects on the nozzle opening pressure but that the diameter of the piston, the initial fuel temperature and the residual volume greatly influence the nozzle opening pressure.

The results of angular and range estimation by conventional signal processing will be far away from true values in the case of unresolved targets due to the merged measurement. In this article, the authors propose a method to localise unresolved targets for frequency diverse array (FDA) radar. Adopting the configurations of subarray-based FDA and full-band FDA as transmitter and receiver, the transmit and receive beampatterns of system are both decoupled in range and angle demands. Furthermore, the receive beamwidth is only a quarter of transmit in range. With the wide transmit beam and narrow receive beam, the authors divide the resolution cell containing unresolved targets into four parts to process separately. A method of intra-pulse beam scanning is proposed to suppress the interference from the targets out of receive beam. Several simulation results demonstrate the effectiveness of the proposed method in the localisation of unresolved targets.

This paper studies the secure state estimation problem of linear time-varying Gaussian processes in the presence of stochastic noises based on measurements from a set of sensors, a subset of which can be compromised by an attacker. The measurement of the compromised sensors can be arbitrarily manipulated by the attacker. We first show that in the absence of attacks, the Kalman filter can be decomposed into m local estimators and the Kalman estimate can be obtained by summing up the local estimates. We further show a least square interpretation to the fusion process and based on which, a convex optimization based secure state estimation scheme is proposed. The secure state estimation algorithm guarantees that when all the sensors are benign, the secure estimate coincides with the Kalman estimate. When less than half of the sensors are compromised, the secure state estimation scheme can still generate an estimate with bounded estimation error. Moreover, we demonstrate how to formulate the convex optimization problem to a conic programming problem to facilitate the application of the proposed secure state estimation algorithm in embedded systems. In the end, numerical simulations are conducted to verify the effectiveness of the proposed algorithm.

In this technical brief, we provide an asynchronous modified repetitive controller design to address the periodic trajectory tracking problem for switched systems with time-varying switching delays between plant modes and controllers. In the feedback channel, a dynamic output feedback mechanism is adopted. By utilizing the lifting technique, the dynamic output feedback-based switched repetitive control system is transformed into a continuous-discrete two-dimensional (2D) model to differentiate the control and learning actions involved in the repetitive controller. For the transformed 2D model, by constructing a piecewise Lyapunov functional and utilizing a matrix decomposition approach, sufficient conditions in terms of linear matrix inequalities (LMIs) and the average dwell time are developed to guarantee closed-loop exponential stability. The performance of the proposed approach is illustrated via a switched RLC series circuit example and numerical simulations are provided.

We consider that there exist delays and random packet dropouts (PDs) in the communication network. Based on this background, this paper focuses on the stochastic stability for networked Markovian switching systems (NMSS). The modes of NMSS and desired controller do not need to synchronize, and they are determined by two mutually independent Markov chains, respectively. A sufficient condition is derived such that the closed-loop NMSS can be stochastically stable. A numerical example and simulations show the effectiveness of the proposed approach.

The frequency diverse array (FDA) has drawn substantial attention because it provides a new degree of freedom. However, the multitarget localization is fundamentally limited by the range-angle-coupled and range-periodic beampattern of the basic FDA. It has been suggested to design a special FDA configuration to localize targets, but seldom of the existing works consider the design both in transmitting and receiving. In this paper, a transmit&ndash, receive system of FDA radar is proposed for the multitarget localization. In order to decouple the beampattern in the range and angle domains, the configurations of subarray-based FDA (SB-FDA) and full-band FDA (FB-FDA) are chosen as transmitter and receiver, respectively. In such a system framework, the receive beamwidth in range domain is only a quarter of the transmission. Then, two typical multitarget scenarios, sparse targets and unresolved targets, are both considered in the multitarget localization. For sparse targets, a proper frequency increment is selected to control the range-periodic transmit and receive mainlobes to focus on a single target, besides being staggered with others. In this way, multitarget localization is achieved in different pulses with monopulse processing. For unresolved targets, a method of intra-pulse beam scanning is proposed to localize each target with little interference from others. We also analyze the system performance in Cram&eacute, r-Rao lower bound (CRLB) of localization and output signal to interference-plus-noise ratio (SINR). Several simulation results demonstrate the effectiveness of the proposed transmit&ndash, receive system in multitarget localization.

Prediction of stock index is seen as a challenging task of financial time series prediction. In this study, we proposed a movement trend-based data preparation method, preprocessing the trend indicator in two steps, and modeled stock index using Gated Recurrent Unit (GRU). In the two-stage preprocessing, the trend indicators were extracted from five aspects and then were discretized based on the dynamic relationship. And three Recurrent Neural Networks were applied to forecast financial time series. Compared with random tri-prediction method, our model improved the stock index movement trend prediction from 33% to 68%.

This paper proposes a family of N-Branch hybrid switched inductor and capacitor (SLC) converters. With the single circuit, the multi-level output voltage or current could be generated. The proposed converter is suitable both for the voltage source and the current source. The same LC network is reused for different LC branches. The proposed converter is controlled by the phase shift control method with a time domain multiplexing concept. The N level circuit is operated with the same frequency. One cycle period is divided into N small time cycles for each branch. The phase shift for each branch is 360°/N. The load voltage could be changed by modifying the duty cycle of the transistor. When the SLCs work in the resonant condition, the soft switching will be acquired. The power loss of transistors could be sharply reduced. In this paper, a 300 W SLC converter is constructed to verify the theoretical analysis and operation mechanism in the resonant condition and hard switching condition. With the experimental and simulated verification, the soft switching and the stable multi-level output voltage or current are achieved. The proposed SLC converter could be used for the multi-level voltage power supply system, such as the electric vehicle, the electric aircraft, autonomous underwater vehicles (AUVs) and a new energy generation system.

This paper presents an investigation combining both experiment and simulation on the sole impacts of the injection pressure p in on the inner cavitation process, and the effects of the cavitation on the flow capacity of the nozzle. An optical nozzle is designed based on the similarity principle of amplification in an equal proportion, and both the structure and the cavitation number are similar to the baseline nozzle. A numerical model is built to analyse the details of the inner flow. The results show that cavitation occurs as p in increases, and a bubble ring forms. The total flow process is divided into three periods: the no-cavitation, the cavitation developing and the stable cavitation periods. During the no-cavitation period, no bubbles occur, and the discharge coefficient C d is a constant and determined by the nozzle structure. During the cavitation developing period, when p in rises, the area of the bubble ring increases, but C d decreases and is governed by f the cavitation number CN and the cavitation area coefficient K A . During the stable cavitation period, at the inlet the bubble ring reaches the maximum then becomes stable; C d is determined only by CN , and infinitely close to a constant as p in increases.

The exponential stability problem of uncertain neutral complex system with Markovian switching is investigated in the presence of nonlinear perturbations and partial information on transition rates. The study begins to consider the related nominal systems and construct a novel augmented stochastic Lyapunov functional which contains some triple-integral terms to reduce the conservatism. Then the exponential stability criteria are developed by utilizing Lyapunov stability theory, reciprocally convex lemma and free-weighting matrices. The results are further extended to the corresponding uncertain case. Finally, numerical examples are given to illustrate the effectiveness of the proposed methods.

This paper considers the problem of finite-time event-triggered H ∞ control for switched linear systems with time-varying delay and norm-bounded exogenous disturbance. First by employing a state observer, an observer-based event-triggered controller is designed to guarantee the finite-time stabilization of the resulting dynamic augmented closed-loop system. Then based on Lyapunov-like function method and average dwell time technique, some sufficient conditions are given to ensure the finite-time stabilization of the H ∞ control system. A numerical example is finally exploited to verify the effectiveness and potential of the achieved control scheme.