Filter Design Approach Research Articles

H∞ filter design for fuzzy systems with quantized measurements

This paper addresses the problem of H∞ filtering for a class of discrete time T–S model based fuzzy systems with quantized measurements. The measurement signal is quantized by a logarithmic quantizer. By using basis dependent Lyapunov function, a sufficient condition is provided to ensure the stability of the filtering error system and to guarantee a given H∞ performance level. Based on this analysis result of the filtering error system, an explicit filter design approach is proposed and the basis dependent filtering algorithm is further improved by using a kind of relaxed technique. Two numerical examples are also presented to show that the filtering algorithm based on the basis dependent Lyapunov function has less conservative than the one based on the basis independent Lyapunov function.

Effective utilization of cables and transformers using passive filters for non-linear loads

In the literature, it is well known that transformers and cables have excessive losses or overheating under non-sinusoidal current conditions. Accordingly, they have reduced current carrying capabilities (or loading capabilities) for that kind of conditions. This paper aims to employ passive filters for the effective utilization of the cables and transformers in the non-sinusoidal systems. Consequently, an optimal passive filter design approach is provided to maximize the power factor expression, which takes into account frequency-dependent line losses, under non-sinusoidal background voltage and line current conditions. The individual and total harmonic distortion limits placed in IEEE standard 519 are taken into account as constraints for the proposed approach. Besides, keeping the load’s displacement power factor at an adequate range is desired by the proposed approach. The proposed approach and the traditional optimal passive filter design approach, which aims to maximize the classical power factor expression, are comparatively evaluated for an industrial power system with a group of linear and non-linear loads, overhead transmission lines, cables and a transformer. Numerical results show that the proposed one has a considerable advantage in the improvement of the total supply line loss and the transformer’s loading capability under non-sinusoidal conditions when compared to the traditional one. On the other hand, for the simulated system cases, both approaches lead to almost the same current carrying capability value of the cables.

Temporal Coupled-Mode Theory and the Combined Effect of Dual Orthogonal Resonant Modes in Microstrip Bandpass Filters

We propose a temporal coupled-mode theory for the design of microstrip bandpass filters with multi-resonant modes and reveals the mechanism of the filters based on multi-coupling and energy conservation theorem. As an example, the combined effect of the two orthogonal modes in dual-mode filters is analyzed in detail. By simply tuning the coupling efficiencies of the two resonant modes, two K-band integrated microstrip bandpass filters have been designed and demonstrate opposite asymmetric transmission responses. Both simulation and experiment results agree well with the theoretical analysis, which provides a new approach for filter design and optimization.

Voltage Distortion Approach for Output Filter Design for Off-Grid and Grid-Connected PWM Inverters

This paper proposes a novel voltage distortion approach for output filter design based on the voltage transfer function for both off-grid and grid-connected Pulse Width Modulation (PWM) Inverters. The method explained in detail is compared to conventional methods. A comparative analysis is performed on an example of L and LCL-filter design. Simulation and experimental results for the off-grid and the grid-connected single phase inverter prove our theoretical predictions. It was found that conventional methods define redundant values of the output filter elements. Assumptions and limitations of the proposed approach are also discussed.

Data-driven Filter Design for Linear Systems with Quantized Measurements

This paper is concerned with the problem of data-driven filter design for linear systems with bounded noise by using quantized measurements. Since the mathematical model of the plant studied is unavailable, most of the existing model-based filter design approaches cannot be used to solve this problem. Another challenge lies in the fact that all the measurement data accessible is quantized. To solve this issue, a quasi-feasible filter set within the set membership framework is proposed, and a data-driven optimal worst-case filter is designed. Furthermore, an l2-l∞ almost-optimal worst-case filter design algorithm is presented by means of linear programming technique. A numerical example is given to illustrate the effectiveness of the proposed algorithms.

Fault detection in finite frequency domains for multi‐delay uncertain systems with application to ground vehicle

SummaryThis paper is concerned with the actuator fault detection (FD) problem in finite frequency domains for multi‐delay systems subject to time‐varying affine uncertainties. Because of the existence of time‐varying uncertain parameters, the generalized Kalman–Yakubovic–Popov lemma based finite frequency FD filter design approaches cannot be applied. To tackle this difficulty, a new delay‐dependent bounded real lemma (BRL) is established by using Lyapunov theory and Parseval's theorem to characterize the finite frequency disturbance attenuation and fault sensitivity performances. Moreover, via the obtained BRL, convex FD filter design conditions are then derived by constructing a hyperplane tangent. Finally, the effectiveness and advantages of the proposed FD method are illustrated through a simulation example on a ground vehicle. Copyright © 2014 John Wiley & Sons, Ltd.

Optimal analog active filter design using craziness‐based particle swarm optimization algorithm

SummaryBecause of the manufacturing constraints, the optimal selection of passive component values for the design of analog active filter is very critical. As the search on possible combinations in preferred values for capacitors and resistors is an exhaustive process, it has to be automated with high accuracy within short computation time. Evolutionary computation may be an attractive alternative for automatic selection of optimal discrete component values such as resistors and capacitors for analog active filter design. This paper presents an efficient evolutionary optimization approach for optimal analog filter design considering different topologies and manufacturing series by selecting their component values. The evolutionary optimization technique employed is craziness‐based particle swarm optimization (CRPSO). PSO is very simple in concept, easy to implement and computationally efficient algorithm with two main advantages: fast convergence and only a few control parameters. However, the performance of PSO depends on its control parameters and may be influenced by premature convergence and stagnation problem. To overcome these problems, the PSO algorithm has been modified to CRPSO and is used for the selection of optimal passive component values of fourth‐order Butterworth low‐pass analog active filter and second‐order state variable low‐pass filter, respectively. CRPSO performs the dual task of efficiently selecting the component values as well as minimizing the total design errors of low‐pass active filters. The component values of the filters are selected in such a way so that they become E12/E24/E96 series compatible. The simulation results prove that CRPSO efficiently minimizes the total design error with respect to previously used optimization techniques. Copyright © 2014 John Wiley & Sons, Ltd.

Fault Detection for Discrete Systems With Network-Induced Nonlinearities

This paper addresses the fault detection filtering issue for a class of discrete system with network-induced nonlinear characteristics. The communication limitations, including measurements quantization, signal transmission delay, and data packet dropout, frequent in many practical networked control systems (NCSs) are considered. By transforming the residual system into an input-output form consisting two interconnected subsystems via a two-term approximation to the state delay variables, sufficient conditions are established. Under these conditions, the residual system is stochastically stable with a prescribed $\mathcal{H}_{\infty}$ level with the help of the scaled small gain (SSG) theorem developed for stochastic systems. Furthermore, the fault detection filter design approach is presented. A numerical example is also provided to demonstrate the effectiveness of the proposed method.

Optimal C-Type Filter Design to Maximize Transformer's Loading Capability under Non-sinusoidal Conditions

The main purpose of this article is to employ the C-type passive filters for maximization of the loading capability of transformers under non-sinusoidal conditions. For this aim, an optimal passive filter design approach is proposed regarding minimization of the harmonic loss factor (FHL), which is defined in IEEE standard C57.110 to represent the loading capability of the transformers supplying non-sinusoidal load currents. With respect to IEEE standard 519, displacement power factor and individual harmonics & total harmonic distortions of the voltage and current are considered as constraints of the proposed optimal filter design approach. In addition, numerical results are presented to figure out that the proposed approach provides higher loading capability of the transformers under non-sinusoidal conditions when compared with the other two optimal filter design approaches based on minimization of the current total harmonic distortion and minimization of the voltage total harmonic distortion.

A novel approach to unknown input filter design for discrete-time linear systems

In this paper, a new H∞ filter design approach is proposed for discrete-time linear systems with unknown inputs. The proposed Lyapunov-based approach, free of any similarity transformations, designs a linear filter for the modified model of the plant, and then extracts the original states of the system. The designed filter estimates both the system states and the unknown input simultaneously and does not have many of the restrictive assumptions and restrictions that the existing unknown input filters do. In the end, simulation results are used to illustrate the effectiveness of the proposed filter.

Particle Swarm Optimization with Aging Leader and Challengers for Optimal Design of Analog Active Filters

Due to the manufacturing limitations, the task of optimal analog active filter design by hand is very difficult. Evolutionary computation may be a competent implement for automatic selection of optimal discrete component values such as resistors and capacitors for analog active filter design. This paper presents an efficient approach for optimal analog filter design considering different topologies and manufacturing series by selecting their component values. The evolutionary optimization technique used is particle swarm optimization (PSO) with Aging Leader and Challenger (ALC-PSO). ALC-PSO performs the dual-task of efficiently selecting the component values as well as minimizing the total design errors of low pass active filters. The component values of the filters are selected in such a way so that they become E12/E24/E96 series compatible. The simulation results prove that ALC-PSO efficiently minimizes the total design error with respect to previously used optimization techniques.

An efficient hybrid genetic algorithm to design finite impulse response filters

Although genetic algorithms (GAs) have proved their ability to provide answers to the limitations of more conventional methods, they are comparatively inefficient in terms of the time needed to reach a repeatable solution of desired quality. An inappropriate selection of driving parameters is frequently blamed by practitioners. The use of hybrid schemes is interesting but often limited as they are computationally expensive and versatile. This paper presents a novel hybrid genetic algorithm (HGA) for the design of digital filters. HGA combines a pure genetic process and a dedicated local approach in an innovative and efficient way. The pure genetic process embeds several mechanisms that interact to make the GA self-adaptive in the management of the balance between diversity and elitism during the genetic life. The local approach concerns convergence of the algorithm and is highly optimized so as to be tractable. Only some promising reference chromosomes are submitted to the local procedure through a specific selection process. They are more likely to converge towards different local optima. This selective procedure is fully automatic and avoids excessive computational time costs as only a few chromosomes are concerned. The hybridization and the mechanisms involved afford the GA great flexibility. It therefore avoids laborious manual tuning and improves the usability of GAs for the specific area of FIR filter design. Experiments performed with various types of filters highlight the recurrent contribution of hybridization in improving performance. The experiments also reveal the advantages of our proposal compared to more conventional filter design approaches and some reference GAs in this field of application.

A new delay-range-dependent H∞ filter design for T–S nonlinear systems

This paper focuses on the problem of H∞ filter design for continuous-time Takagi and Sugeno (T–S) fuzzy systems with time-varying delays. The partitioning time delay technique is used to construct the Lyapunov–Krasovskii functional, furthermore, a novel delay-dependent H∞ filter design approach is proposed based on the matrix decoupling approach, and the filter parameters can be obtained by solving a set of linear matrix inequalities (LMIs). The numerical examples show that the proposed method is of less conservativeness than the existing methods.

Robust estimation for discrete time‐delay Markov jump systems with sensor non‐linearity and missing measurements

This study addresses the ℋ∞ filtering design issue for a class of time-delay Markov jump system with non-linear characteristics. A stochastic system with sensor saturation and intermittent measurements is considered in the authors study. Random noise depending on state and external-disturbance are also taken into account. A decomposition approach and a bernoulli process are utilised to model the characteristic of sensor saturation and missing measurements, respectively. By transforming the filtering error system into an input–output form, sufficient conditions for the stochastic stability of the system with a prescribed ℋ∞ level are presented with the help of Scaled Small Gain theorem developed for stochastic systems. Based on the proposed conditions, the rubost filter design approach is proposed. A numerical example is finally provided to demonstrate effectiveness of the proposed approahc.

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A novel concept of bandpass filter (BPF) using distributed stub loaded highpass filter (HPF) and Defected Microstrip Structure (DMS) is proposed in this paper, which exhibits an ultra-wideband (UWB) property. The proposed design exhibits a bandpass response with WLAN rejection by combining the proposed DMS with the highpass filter design approach, also miniaturization is proposed to minimize the structure resulting in the pass band enhancement of the proposed filter with minimum insertion loss. The design consists of shorted stub microstrip transmission line on a substrate with relative dielectric constant 4.4 and thickness 1.59 mm. Its excellent bandpass property is verified by both simulated and measured results which show a result of 90.39% Fractional Bandwidth (FBW). The proposed UWB- BPF has an advantage of compact size, low cost and easy fabrication.

The Optimization Problems of Transmit and Receive Design for Radar Operating in Littoral Zones

The complex environments of the littoral zones prevent the radar from operating efficiently. We propose a waveform and filter design approach to help the radar improve the performance in littoral zones. The approach includes a phase-only nonlinear programming method for suppressing correlation sidelobes in specified Doppler and range intervals, and an alternating projection based algorithm for designing receive filters. Several numerical examples are provided to demonstrate the usage and effectiveness of the proposed methods.

Randomized Approaches for Control of QuadRotor UAVs

A systematic mixed deterministic-randomized approach for filter design is presented. This method has two advantages: (i) it is a computational efficient algorithm for the deterministic parameters and (ii) we can design fixed order controllers because we follow a randomization approach. Different filter forms are selected to prove the effectiveness of this algorithm and the obtained results are applied to a multi rotor UAV. Both linear and experimental models are analyzed. For the linear case a comparison with a LQR controller is proposed to prove that with this filter the designed controller permits to minimize the noise due to the coupling effects between the different control axes. This design is useful to reduce the set up time of an adaptive controller filter if different maneuvers or aircraft parameters are considered.

Introduction to the special issue on Low-power circuit techniques

This special issue of ‘‘Low-power circuit techniques’’ in the Springer Journal of Analog Integrated Circuits and Signal Processing is published with six papers, which are selected from presented papers at the 2012 International Conference on Analog VLSI Circuits (AVIC 2012). This conference is believed to be the only conference that bares the key word ‘‘Analog VLSI’’, and have accepted very wide range of papers concerning analog circuits. Among them, we called for papers related to low-power circuit techniques for this special issue. The Research Committee on Electronic Circuits of the Institute of Electrical Engineers of Japan (IEEJ) was sponsoring and cooperating with Analog Devices Inc., the University of Valencia and the Polytechnic University of Valencia to hold the 2012 International Conference on Analog VLSI Circuits in Valencia, Spain, on October 24–26, 2012. This conference is the successor of former International Analog VLSI Workshop, which had been successfully held for 14 years. The purpose of the conference is to exchange information, ideas and recent research results on analog VLSI circuits and their applications. This workshop has formed a long-standing community for various analog VLSI circuit specialists from both industry and academia worldwide, and promoted active brainstorming among them at the site. The first two papers are related to power supply circuits and DC–DC converter circuits. The first paper by Nomura et al. presents photovoltaic cell design, oscillator, and bootstrap charge pump circuit integrated on an 0.18 lm CMOS chip, to provide power generation and voltage boost functions on stand-alone microsystems. Sato et al. present a theoretical analysis of efficiency in charge pumps for LED drivers and describe a novel procedure to minimize power loss by applying adiabatic process to charge pump circuits. The third paper by Tanimoto et al. presents a fullydifferential OTA operating from 1-V power supply. The OTA consists from CMOS cascode inverters to obtain a high voltage gain while maintaining rail-to-rail input common-mode range at 1-V power supply. They also fabricated a test chip by using 0.15 lm CMOS technology and confirmed the design techniques to be useful. The fourth and the fifth papers are concerning to high speed communication signal processing. Nakagawa et al. present a passive complex filter design approach, which is relevant to low power analog signal processing at very high frequency. The concept is exemplified with two complex filters operating at 100 kHz and 10 MHz but maybe extended beyond tens of GHz. The fifth paper by Yazaki et al. presents a design of a 20-Gbps CMOS optical receiver, which does not require inductor to suppress power supply noise by a unique design of power supply noise canceling circuit. The designed chip was fabricated in 90 nm CMOS technology and demonstrated effectiveness of the design. The last paper by Carbajo et al. presents a new version of the well known Goertzel algorithm for discrete Fourier J. Calpe-Maravilla Analog Devices S.L., Edificio 8F, Planta 3, Campus UPV, 46022 Valencia, Spain e-mail: javier.calpe@analog.com

Switching-Type $H_{\infty }$ Filter Design for T–S Fuzzy Systems With Unknown or Partially Unknown Membership Functions

This paper is concerned with the H∞ filter design problem for Takagi-Sugeno (T-S) fuzzy systems with unknown or partially unknown membership functions. If the membership functions are allowed to be unknown or partially unknown, then a fuzzy system may describe a wide class of nonlinear systems. However, in this case, the filter design of fuzzy systems, which is based on parallel distributed compensator strategy, is infeasible. To tackle this difficulty, a switching mechanism, which depends on the lower and upper bounds of the unknown membership functions, is introduced to construct the H∞ filter with varying gains. Some examples given in the simulation section show that the proposed method can achieve a better disturbance attenuation performance than a simple fixed-gain filter design approach.

Gain-Constrained Recursive Filtering With Stochastic Nonlinearities and Probabilistic Sensor Delays

This paper is concerned with the gain-constrained recursive filtering problem for a class of time-varying nonlinear stochastic systems with probabilistic sensor delays and correlated noises. The stochastic nonlinearities are described by statistical means that cover the multiplicative stochastic disturbances as a special case. The phenomenon of probabilistic sensor delays is modeled by introducing a diagonal matrix composed of Bernoulli distributed random variables taking values of 1 or 0, which means that the sensors may experience randomly occurring delays with individual delay characteristics. The process noise is finite-step autocorrelated. The purpose of the addressed gain-constrained filtering problem is to design a filter such that, for all probabilistic sensor delays, stochastic nonlinearities, gain constraint as well as correlated noises, the cost function concerning the filtering error is minimized at each sampling instant, where the filter gain satisfies a certain equality constraint. A new recursive filtering algorithm is developed that ensures both the local optimality and the unbiasedness of the designed filter at each sampling instant which achieving the pre-specified filter gain constraint. A simulation example is provided to illustrate the effectiveness of the proposed filter design approach.