A multi-tone central divided difference frequency tracker with adaptive process noise covariance tuning

The problem of real-time frequency estimation of nonstationary multi-harmonic signals is important in many applications. In this paper, we propose a novel multi-frequency tracker based on a state-space representation of the signal with Cartesian filters and the second-order central divided difference filter (CDDF), which improves the performance of the extended Kalman filter (EKF) by using Stirling's interpolation method to approximate the mean and covariance of the state vector. A crucial element of the method is the adaptive scaling of the process noise covariance matrix appearing in the filter equations, as a function of the innovation sequence, which tunes the accuracy-reactivity trade-off of the filter. The proposed solution is evaluated against two approaches from the literature, namely the factorized adaptive notch filter (FANF) and the extended Kalman filter frequency tracker (EKFFT). Several experiments emphasize the estimation accuracy of the proposed method as well as the improved robustness with respect to initial errors and input signal complexity. The presented method appears to be particularly efficient with rapidly varying frequencies, thanks to the update mechanism that adjusts the filter parameters based on the amplitude of the estimation error.     

Manufacturing of nano mullite-silicon carbide filters by in situ reaction bonding

In the present study, the effect of silica nanoparticles on the formation of nano-mullite phase for use in the manufacture of silicon carbide based ceramic foam filters has been investigated. Polyurethane foam filters were impregnated with nanosilica particles by slip casting. In this method, the effect of different percentages of nanosilica particles in the slurry on compressive strength, density and porosity of ceramic foam filters was investigated. The effect of silica nanoparticles on viscosity of slurry was studied using rheometric test. So, sample S₁₅ was selected to proceed. For thermal treatment of ceramic foams, different sintering temperatures were investigated and the best temperature was reported at 1250 °C. Compressive strength results showed that with increasing nano-silica content, CCS increased. XRD results from the samples showed that the nano-mullite phase was formed at 1250 °C along with silicon carbide and alumina phases. Scanning electron microscope images (SEM) showed that the mullite phase was formed in nano-dimensions in ceramic foam bodies. The formation of mullite phase in the microstructure of the filters is one of the factors of strengthening and increased refractory characteristics. EDS analysis by the scanning electron microscopy of the filter which passed ductile iron melt showed that cast iron inclusions and impurities were mostly consisted from FeO, MnO, SiO₂, Al₂O₃, MgO and CO, which were trapped inside the ceramic filter.     

Evaluation of fluctuating voltage topology with fuel cells and supercapacitors for automotive applications

To develop a single‐stage power conversion topology in which energy storage devices can be directly coupled, a fluctuating voltage topology is applied, leading to lower cost and more compactness with the absence of DC/DC converters. This paper investigates such a topology for automotive applications where fuel cells are directly connected to the DC bus of the inverter, resulting in fluctuating voltage across the DC bus. Further, a supercapacitor pack is also introduced to maintain the power capacity and voltage stability. The hybridization principle and practical application of such a topology are then discussed in the time domain and frequency domain. Furthermore, the transient power requirement is decomposed to design the size of fuel cells and supercapacitors. Simulation results from the modeling of the fuel cell‐supercapacitor powertrain demonstrate the feasibility and effectiveness of this topology. The supercapacitors can serve as a low‐pass filter for the fuel cells. In conclusion, the peak power requirement can be successfully achieved because of the lowered system impedance, and the fuel cells only need to supply the average power.     

Joint model of gradient magnitude and Gabor features via Spatio-Temporal slice

To form a high-performance video quality predictor, we developed a framework for full-reference (FR) video quality assessment that integrates Spatio-temporal slice analysis (STS) to create a high-performance predictor of video quality. However, both gradient and Gabor are spatial–temporal structural capturers used for the simultaneous extraction of both spatial and temporal features. In this paper, we proposed a novel VQA algorithm via a joint model of gradient magnitude and Gabor features (JMG) between the STS images of the reference videos and their distorted counterparts to assess the degradation of video quality effectively. Firstly, gradient magnitude and the Gabor filter were constructed to extract the spatiotemporal features of the video sequence. However, the two-feature model combined to predict the perceptual quality of frames. This new proposed VQA model is known as the horizontal and time STS (HT-JMG) model. To further investigate the influence of spatial dissimilarity, we combined the frame-by-frame spatial T-JMG(S) factor with the HT-JMG and propose another VQA model, called the time, horizontal, and vertical STS (THV-JMG) model. Finally, the results of the experiment showed that the proposed method has a strong correlation with subjective perception and is competitive with state-of-the-art full reference VQA models.     

On‐site wastewater treatment using reactive filter media

The aim of this study is to reduce the phosphate concentration in treated wastewater using a small amount of the reactive filter media, Filtralite P. Biologically treated wastewater was passed through a filter with 215 g of Filtralite P. In the laboratory, the phosphate removal efficiency was 51% at a flow speed of 0.87 m/h. Under real conditions, in an experimental stand filled with 0.5 m³ of Filtralite P, the phosphate removal efficiency was 85% and the removal efficiency of total suspended solids was 57% after a 5‐month period. The residual phosphate concentration in the filtrate from the experimental stand was 1 mg/L of PO₄‐P after the 5‐month period. The experimental filtration plant was buried in the ground, and it did not freeze and worked well under winter conditions. The results of this study can be useful in the design and development of tertiary wastewater treatment plants in view of their sustainability potential.     

Full and reduced-order H∞ filtering of Takagi–Sugeno fuzzy time-varying delay systems: Input–output approach

This article addresses the issue of delay-dependent H_∞ filtering design for TakagiŮSugeno fuzzy time-varying delay systems using the input–output approach. A three-term approximation model has been used to transform the original system into two interconnected subsystems. Since the nonquadratic Lyapunov–Krasovskii functional requires to deal with the membership function's (MF) time derivative, upper-bound inequalities have been added to the obtained conditions. Based on the scaled small gain theorem, nonquadratic Lyapunov–Krasovskii functional approach and considering the bounds of the MF time-derivative, the H_∞ full- and reduced-order filters are designed and then formulated in terms of linear matrix inequalities. Finally, illustrative examples are presented to demonstrate the validity of the proposed methods.     

Dynamic load-altering attack detection based on adaptive fading Kalman filter in power systems

This paper presents an effective and feasible method for detecting dynamic load-altering attacks (D-LAAs) in a smart grid. First, a smart grid discrete system model is established in view of D-LAAs. Second, an adaptive fading Kalman filter (AFKF) is designed for estimating the state of the smart grid. The AFKF can completely filter out the Gaussian noise of the power system, and obtain a more accurate state change curve (including consideration of the attack). A Euclidean distance ratio detection algorithm based on the AFKF is proposed for detecting D-LAAs. Amplifying imperceptible D-LAAs through the new Euclidean distance ratio improves the D-LAA detection sensitivity, especially for very weak D-LAA attacks. Finally, the feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified based on simulations.     

Observer‐based fuzzy adaptive quantized control for uncertain nonlinear multiagent systems

This paper focuses on consensus quantized control design problem for uncertain nonlinear multiagent systems with unmeasured states. Every follower can be denoted through a system with unmeasurable states, hysteretic quantized input, and unknown nonlinearities. Fuzzy state observer and Fuzzy logic systems are employed to estimate unmeasured states and approximate unknown nonlinear functions, respectively. The hysteretic quantized input can be split into two bounded nonlinear functions to avoid chattering problem. By combining adaptive backstepping and first‐order filter signals, an observer‐based fuzzy adaptive quantized control scheme is designed for each follower. All signals exist in closed‐loop systems are semiglobally uniformly ultimately bounded, and all followers can accomplish a desired consensus results. Finally, a numerical example is employed to elaborate the effectiveness of proposed control strategy.     

Retracted: State estimation of Takagi-Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

This article concerns the event-triggered fuzzy filter design for Takagi-Sugeno (T-S) fuzzy systems subject to deception attacks under the stochastic multiple time-varying delays. A sequence of random variables, which are mutually independent but obey the Bernoulli distribution, is introduced to account for the randomly occurring communication delays. In order to efficiently utilize limited network communication bandwidth resources, the event-triggering scheme is adopted. A fuzzy filter with the attacked input signal is presented. Moreover, due to communication delays caused by event-triggering schemes and transmission, the filter adopts non-synchronous premise variables with the system. Then, by utilizing a model transformation technique, the fuzzy systems are developed. Furthermore, using the piecewise Lyapunov functional method technique, the resulting criterion provides sufficient conditions to ensure that fuzzy systems under deception attacks are stochastically stable with an H_∞ performance. Accordingly, the conditions for the co-design of the fuzzy filter and event-triggering schemes are given. Finally, numerical simulation with the industrial process provided to verify the proposed event-triggered design.     

地磁图数据随机误差建模与补偿

地磁图是影响地磁匹配导航性能的重要因素,其中地磁图的随机误差严重影响匹配定位精度,甚至导致误匹配。 为提 高地磁匹配性能,提出了地磁图数据随机误差建模与补偿方法。 该方法在对地磁图数据随机误差特性分析的基础上,建立数据 的非平稳时间序列模型,并将此模型作为状态方程,以实时数据为量测量,采用 Kalman 滤波方法对地磁图数据进行滤波,补偿 地磁图数据的随机误差。 通过基于滤波前后地磁图数据的导航定位实验,间接证明滤波方法的有效性。 对实际地磁图数据处 理结果表明,应用该方法滤波后的地磁图数据进行导航,其定位精度提高了 54. 7%。