Showing papers on "Filter design published in 2016"

Dissipativity-Based Filtering for Fuzzy Switched Systems With Stochastic Perturbation

Abstract: In this technical note, the problem of the dissipativity-based filtering problem is considered for a class of T-S fuzzy switched systems with stochastic perturbation. Firstly, a sufficient condition of strict dissipativity performance is given to guarantee the mean-square exponential stability for the concerned T-S fuzzy switched system. Then, our attention is focused on the design of a filter to the T-S fuzzy switched system with Brownian motion. By combining the average dwell time technique with the piecewise Lyapunov function technique, the desired fuzzy filters are designed that guarantee the filter error dynamic system to be mean-square exponential stable with a strictly dissipative performance, and the corresponding solvability condition for the fuzzy filter is also presented based on the linearization procedure approach. Finally, an example is provided to illustrate the effectiveness of the proposed dissipativity-based filter technique.

Filtering of Interval Type-2 Fuzzy Systems With Intermittent Measurements

Abstract: In this paper, the problem of fuzzy filter design is investigated for a class of nonlinear networked systems on the basis of the interval type-2 (IT2) fuzzy set theory. In the design process, two vital factors, intermittent data packet dropouts and quantization, are taken into consideration. The parameter uncertainties are handled effectively by the IT2 membership functions determined by lower and upper membership functions and relative weighting functions. A novel fuzzy filter is designed to guarantee the error system to be stochastically stable with $\boldsymbol {H_{\infty }}$ performance. Moreover, the filter does not need to share the same membership functions and number of fuzzy rules as those of the plant. Finally, illustrative examples are provided to illustrate the effectiveness of the method proposed in this paper.

Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System

Abstract: This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered ${H} _{{\infty }}$ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.

Deep beamforming networks for multi-channel speech recognition

Abstract: Despite the significant progress in speech recognition enabled by deep neural networks, poor performance persists in some scenarios. In this work, we focus on far-field speech recognition which remains challenging due to high levels of noise and reverberation in the captured speech signals. We propose to represent the stages of acoustic processing including beamforming, feature extraction, and acoustic modeling, as three components of a single unified computational network. The parameters of a frequency-domain beam-former are first estimated by a network based on features derived from the microphone channels. These filter coefficients are then applied to the array signals to form an enhanced signal. Conventional features are then extracted from this signal and passed to a second network that performs acoustic modeling for classification. The parameters of both the beamforming and acoustic modeling networks are trained jointly using back-propagation with a common cross-entropy objective function. In experiments on the AMI meeting corpus, we observed improvements by pre-training each sub-network with a network-specific objective function before joint training of both networks. The proposed method obtained a 3.2% absolute word error rate reduction compared to a conventional pipeline of independent processing stages.

Generalized Hampel Filters

Abstract: The standard median filter based on a symmetric moving window has only one tuning parameter: the window width. Despite this limitation, this filter has proven extremely useful and has motivated a number of extensions: weighted median filters, recursive median filters, and various cascade structures. The Hampel filter is a member of the class of decsion filters that replaces the central value in the data window with the median if it lies far enough from the median to be deemed an outlier. This filter depends on both the window width and an additional tuning parameter t, reducing to the median filter when t=0, so it may be regarded as another median filter extension. This paper adopts this view, defining and exploring the class of generalized Hampel filters obtained by applying the median filter extensions listed above: weighted Hampel filters, recursive Hampel filters, and their cascades. An important concept introduced here is that of an implosion sequence, a signal for which generalized Hampel filter performance is independent of the threshold parameter t. These sequences are important because the added flexibility of the generalized Hampel filters offers no practical advantage for implosion sequences. Partial characterization results are presented for these sequences, as are useful relationships between root sequences for generalized Hampel filters and their median-based counterparts. To illustrate the performance of this filter class, two examples are considered: one is simulation-based, providing a basis for quantitative evaluation of signal recovery performance as a function of t, while the other is a sequence of monthly Italian industrial production index values that exhibits glaring outliers.

Unimodular Sequence Design Based on Alternating Direction Method of Multipliers

Abstract: The topic of probing waveform design has received considerable attention due to its numerous applications in active sensing. Apart from having the desirable property of constant magnitude, it is also anticipated that the designed sequence possesses low sidelobe autocorrelation and/or specified spectral shape. In this paper, the alternating direction method of multipliers (ADMM), which is a powerful variant of the augmented Lagrangian scheme for dealing with separable objective functions, is applied for synthesizing the probing sequences. To achieve impulse-like autocorrelation, we formulate the design problem as minimizing a nonlinear least-squares cost function in the frequency domain subject to the constraint that all sequence elements are of unit modulus. Via introducing auxiliary variables, we are able to separate the objective into linear and quadratic functions where the unimodular constraint is only imposed on the former, which results in an ADMM-style iterative procedure. In particular, fast implementation for the most computationally demanding step is investigated and local convergence of the ADMM method is proved. To deal with the spectral shape requirement, we borrow the concept in frequency-selective filter design where passband and stopband magnitudes are bounded to formulate the corresponding optimization problem. In this ADMM algorithm development, unit-step functions are utilized to transform the multivariable optimization into a quadratic polynomial problem with a single variable. The effectiveness of the proposed approach is demonstrated via computer simulations.

$H_{\infty }$ Fault Detection for Networked Mechanical Spring-Mass Systems With Incomplete Information

Abstract: This paper focuses on the $H_{\infty }$ fault detection (FD) problem for spring-mass systems (SMSs) over networks with distributed state delays, random packet losses, sensor saturation as well as multiplicative noises via unreliable communication channels. The output measurements are affected by sensor saturation which is described by sector-nonlinearities. The multiplicative noises are described as a form of Gaussian white noises multiplied by the states. A series of stochastic variables are introduced to describe the randomly occurring distributed state delays. Random packet losses are also introduced in unreliable communications. The purpose of this paper is to design an FD filter such that: 1) The FD dynamic system is exponentially stable in the mean square. 2) The error between the fault signal and the residual signal is controlled to the minimum. 3) The optimal $H_{\infty }$ filtering performance index is achieved. A sufficient condition for the FD filter design is derived in terms of the solution to a linear matrix inequality (LMI). When the LMI has a feasible solution, the explicit parameters of the desired FD filter can be obtained. Finally, a simulation experiment is illustrated to show the effectiveness and application of the designed method.

Optimal Estimation in UDP-Like Networked Control Systems With Intermittent Inputs: Stability Analysis and Suboptimal Filter Design

Abstract: We investigate the optimal estimation problem in lossy networked control systems where the control packets are randomly dropped without acknowledgment to the estimator. Most existing results for this setup are concerned with the design of controller, while the optimal estimation and its performance evaluation have been rarely treated. In this paper, we show that, unlike many other cases such as intermittent observations or TCP-like systems, the system state follows a Gaussian mixture distribution with exponentially increasing terms, which leads to a Gaussian sum filter-based optimal estimation. We develop an auxiliary estimator method to establish necessary and sufficient conditions for the stability of the mean estimation error covariance matrices. It is revealed that the stability is independent of the packet loss rate, and is not affected by the lack of acknowledgment. A suboptimal filtering algorithm with improved computational efficiency is then developed. Numerical examples and simulations are employed to illustrate the theoretical results.

Fast Kalman-Like Optimal Unbiased FIR Filtering With Applications

Abstract: In this paper, an optimal unbiased finite impulse response (OUFIR) filter is proposed as a linking solution between the unbiased FIR (UFIR) filter and the Kalman filter (KF). We first derive the batch OUFIR estimator to minimize the mean square error (MSE) subject to the unbiasedness constraint and then find its fast iterative form. It is shown that the OUFIR filter is full horizon (FH) and that its estimate converges to the KF estimate by increasing the horizon length $N$ . As a special feature, we note that the FH OUFIR filter operates almost as fast as the KF. Several other critical properties of the OUFIR filter are illustrated based on simulations and practical applications. Similar to the UFIR filter, and contrary to the KF, the OUFIR filter is highly insensitive to the initial conditions. It has much better robustness than KF against temporary model uncertainties. Finally, the OUFIR filter allows for ignoring system noise, which is typically not well known to the engineer.

Quarter-Mode Cavity Filters in Substrate Integrated Waveguide Technology

Abstract: This paper presents a systematic investigation of quarter-mode filters in substrate integrated waveguide (SIW) technology. This class of filters is particularly convenient because it combines the features of SIW structures with the improvement of size reduction. After a thorough analysis of the quarter-mode SIW cavity, this paper presents different coupling mechanisms and feeding techniques for the design of quarter-mode SIW filters: side coupling and corner coupling are considered, highlighting the advantages and disadvantages of the two techniques. Novel filter topologies are introduced, with the design and experimental verification of simple filters and their extension to higher order filter structures. Techniques to introduce transmission zeros are described and demonstrated. Moreover, the combination of quarter-mode SIW cavities and coplanar waveguide resonators leads to increasing the filter order to higher order and allows the implementation of quasi-elliptic filters.

Design of LCL Filters With LCL Resonance Frequencies Beyond the Nyquist Frequency for Grid-Connected Converters

Abstract: This paper proposes a novel LCL filter design method and its current control for grid-connected converters. With the proposed design method, it is possible to set the resonance frequency of the LCL filter to be higher than the Nyquist frequency, i.e., half of the system sampling frequency, and this observation is so far not discussed in the literature. In this case, a very cost-effective LCL filter design can be achieved for the grid-connected converters, whose dominant switching harmonics may appear at double the switching frequency, e.g., in unipolar-modulated three-level full-bridge converters and 12-switch-based three-phase pulsewidth-modulated converters. Moreover, a single-loop current control strategy is proposed for the designed LCL filter, and the control system is inherently stable without introducing any passive or active damping. Based on the new stability region, two LCL filter design examples are given, with one of them optimizing the utilization of passive filter inductors, and another one being robust against grid impedance variation. Comprehensive experimental results, showing the high-quality output current and excellent resonance attenuation, are presented in this paper, which are also in very good agreement with those of the simulated ones. These results successfully verify the feasibility of the proposed LCL filter design and its current control.

Application of adaptive Savitzky–Golay filter for EEG signal processing☆

Abstract: Summary A Savitzky–Golay filter typically requires pre-determined values of order and frame size for its fabrication. Generally, a random hit-and-trial method or prior experience is required to determine the suitable values of design parameters. However, the proposed adaptive Savitzky–Golay filter aims to provide a generic framework for optimal design of filter vis-a-vis the order and frame size of the filter. The algorithm uses all the possible combinations of these parameters in a certain range and the correlation coefficient is evaluated in each case to measure the filter efficiency. The parameters which provide the highest correlation coefficient are considered for filter design. In this paper the relative advantages of adaptive Savitzky–Golay filter over the standard models are also discussed. The proposed adaptive model of Savitzky–Golay filter is successfully tested for EEG signal processing.

Wireless Power Transfer With Concurrent 200-kHz and 6.78-MHz Operation in a Single-Transmitter Device

Abstract: This paper proposes a wireless power transfer (WPT) transmitter that can concurrently operate at 200 kHz and 6.78 MHz in order to simultaneously power two receivers operating with different frequency standards. Unlike a dual-resonant single-coil design, the use of two separate coils decouples the design for one frequency from the other, enabling independent selection of inductance and Q -factor to simultaneously maximize efficiency at both frequencies. The two coils then support separate coil drivers, enabling concurrent multistandard operation. Dual-band operation is achieved in the same area as an equivalent single-band design by placing a low-frequency coil within the geometry of a high-frequency coil, where the outer diameter of inner coil is sacrificed only by 1.2 cm in a 12.5 × 8.9-cm2 design. Circuit analysis is presented to identify the eddy current between the two Tx coils and its associated loss, after which an eddy-current filter design is proposed. To validate the proposed design, a dual-mode transmitter, along with two receivers designed at 6.78 MHz and 200 kHz, respectively, have been fabricated. At 25-mm separation, the system is able to simultaneously deliver 9 and 7.4 W with efficiencies of 78% and 70.6% at 6.78 MHz and 200 kHz, respectively.

A Variational Bayesian-Based Unscented Kalman Filter With Both Adaptivity and Robustness

Abstract: This paper proposes a modified unscented Kalman filter (UKF) with both adaptivity and robustness. In the proposed filter, the adaptivity is achieved by estimating the time-varying measurement noise covariance based on variational Bayesian (VB) approximation. The robustness is achieved by modifying the filter update based on Huber’s M-estimation and Gaussian–Newton iterated method. In Gaussian assumptions, the proposed filter has a comparable filtering accuracy with the original UKF and better filtering consistency. When the measurement noise covariance is time-varying and there are outliers in the measurements, the proposed filter can outperform UKF and other adaptive or robust filters (such as VB-based UKF and Huber-based UKF) in terms of both filter accuracy and consistency. The efficacy of the proposed filter is demonstrated through the numerical simulation test and integrated navigation shipborne test.

LLCL -Filtered Grid Converter With Improved Stability and Robustness

Abstract: LLCL filter has been proven to introduce more filtering at the converter switching frequency, while using smaller passive components. However, like other higher order filters, it introduces resonance to the grid when used with a grid converter. Its stability and robustness are also affected by grid impedance variations, making its design more challenging. To address these concerns, a new parameter design method for the LLCL filter has been formulated in this paper, which when enforced, guarantees robust and stable grid current control regardless of how the grid conditions change. It is thus an enhanced method even with no damping added to the grid converter. The method has been applied to the development of an LLCL filter for testing in the laboratory with a 5-kW, 400-V, and 50-Hz grid converter. The method can also be applied to the lower order LCL filter with only a slight modification needed.

A comparative study and review of different Kalman filters by applying an enhanced validation method

Abstract: The Kalman filter is a common state of charge estimation algorithm for lithium-ion cells. Since its first introduction in the application of lithium-ion cells, different implementations of Kalman filters were presented in literature. However, due to non-uniform validation methods and filter tuning parameters, the performance of different Kalman filters is difficult to quantify. On this account, we compare 18 different implementations of Kalman filters with an enhanced validation method developed in our previous work. The algorithms are tested during a low-dynamic, high-dynamic and a long-term current load profile at −10 °C, 0 °C, 10 °C, 25 °C and 40 °C with a fixed set of filter tuning values. To ensure comparability, a quantitative rating technique is used for estimation accuracy, transient behaviour, drift, failure stability, temperature stability and residual charge estimation. The benchmark shows a similar estimation accuracy of all filters with an one and two RC term equivalent circuit model. Furthermore, a strong dependency on temperature during high-dynamic loads is observed. To evaluate the importance of the tuning parameters, the temperature dependency is reduced with an individual filter tuning. It is reasoned, that not only the filter type is significant for the estimation performance, but the filter tuning.

Design of optimal digital FIR filters using evolutionary and swarm optimization techniques

Abstract: Design of optimal filters is an essential part of signal processing applications. It involves the computation of optimal filter coefficients such that the designed filter response possesses a flat passband and up to an infinite amount of stopband attenuation. This study investigates the effectiveness of employing the swarm intelligence (SI) based and population-based evolutionary computing techniques in determining and comparing the optimal solutions to the FIR filter design problem. The nature inspired optimization techniques applied are cuckoo search, particle swarm and real-coded genetic algorithm using which the FIR highpass (HP) and bandstop (BS) optimal filters are designed. These filters are examined for the stopband attenuation, passband ripples and the deviation from desired response. Moreover, the employed optimization techniques are compared on the field of algorithm execution time, t -test, convergence rate and obtaining global optimal results for the design of digital FIR filters. The results reveal that the proposed FIR filter design approach using cuckoo search algorithm outperforms other techniques in terms of design accuracy, execution time and optimal solution.

Fast and Provably Accurate Bilateral Filtering

Abstract: The bilateral filter is a non-linear filter that uses a range filter along with a spatial filter to perform edge-preserving smoothing of images. A direct computation of the bilateral filter requires $O(S)$ operations per pixel, where $S$ is the size of the support of the spatial filter. In this paper, we present a fast and provably accurate algorithm for approximating the bilateral filter when the range kernel is Gaussian. In particular, for box and Gaussian spatial filters, the proposed algorithm can cut down the complexity to $O(1)$ per pixel for any arbitrary $S$ . The algorithm has a simple implementation involving $N+1$ spatial filterings, where $N$ is the approximation order. We give a detailed analysis of the filtering accuracy that can be achieved by the proposed approximation in relation to the target bilateral filter. This allows us to estimate the order $N$ required to obtain a given accuracy. We also present comprehensive numerical results to demonstrate that the proposed algorithm is competitive with the state-of-the-art methods in terms of speed and accuracy.

A Reconfigurable Microwave Combline Filter

Abstract: A general cascaded filter design technique is implemented to get a tunable narrow-band filter response based on the general Chebyshev bandpass filter. A cavity combline microwave filter is fabricated by cascading two asymmetrical filters without using an isolator between them. Tuning is provided by means of the screws on top of each resonator of the cavity combline filter. An optimization is applied to get the desired response. The designed example is presented together with the simulation and measurement results. The measured data are in good agreement with the simulation results.

LCL Grid Filter Design of a Multimegawatt Medium-Voltage Converter for Offshore Wind Turbine Using SHEPWM Modulation

Abstract: The switching frequency of medium-voltage high-power converters is limited to about 1 kHz due to semiconductor junction temperature constraint. The frequency band between the fundamental and carrier frequency is limited to a little more than one decade and the LCL filter design is usually a challenge to meet grid codes for grid-connected applications. Traditional designs focus on the optimization of the filter parameters and different damping circuits. However, this design is very influenced by the modulation technique and produced low-order harmonics. Widely used pulse width modulations (PWM), such as phase disposition PWM (PDPWM), produce low-order harmonics that constraint the design of the filter. Selective harmonic elimination PWM (SHEPWM) can eliminate theses low-order harmonics, enabling a more efficient design of the LCL filter. In this paper, the LCL grid filter of a multimegawatt medium-voltage neutral-point-clamped converter for a wind turbine is redesigned using the SHEPWM modulation. Experimental results demonstrate that the efficiency of the converter, filter, and overall efficiency are increased compared to that obtained with PDPWM.

Reconfigurable Planar Capacitive Coupling in Substrate-Integrated Coaxial-Cavity Filters

Abstract: This paper expands our previous work on planar tunable capacitive coupling structures in substrate-integrated cavities using lumped components. We demonstrate both frequency and bandwidth tunable filters with adjustable transmission zeros (TZs). By the appropriate choice of the absolute and relative strength of magnetic and electric coupling coefficients, we demonstrate: 1) tunable bandwidth and the ability to maintain either a constant absolute bandwidth or a constant fractional bandwidth; 2) adjustable TZ location at a prescribed bandwidth; and 3) the ability to switch OFF the filter with high isolation. Filter design methodologies based on a dispersive coupling structure are presented using lumped circuit models, coupling matrix, and full-wave simulations. With this planar capacitive coupling, it is also convenient to realize cross-coupling in higher order filters to produce additional TZs for rejecting spurious resonances or interferes. Fabricated two-pole filters with one or two TZs and four-pole filters with three or four TZs validate the filter design. A two-pole filter with tunable center frequency and tunable bandwidth along with a four-pole filter with tunable center frequency and tunable TZs are also demonstrated.

Sliding extensive cancellation algorithm for disturbance removal in passive radar

Abstract: In this paper an advanced version of the extensive cancellation algorithm (ECA) is proposed for robust disturbance cancellation and target detection in passive radar. Firstly some specific limitations of previous ECA versions are identified when dealing with a highly time-varying disturbance scenario in the presence of slowly moving targets. Specifically, the need to rapidly adapt the filter coefficients is shown to yield undesired effects on low Doppler target echoes, along with the expected partial cancellation. Therefore a sliding version of the ECA is presented which operates on partially overlapped signal batches. The proposed modification to the original ECA is shown to appropriately counteract the limitations above by taking advantage of a smooth estimate of the filter coefficients. An efficient implementation is also discussed to limit the corresponding computational load. The benefits of the proposed approach are demonstrated against real data sets accounting for quite different passive radar applications.