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The distributed state and parameter estimation problem is investigated in this paper for discrete-time nonlinear systems subject to sensor nonlinearities and stochastic disturbances over a wireless sensor network. A novel architecture for distributed state estimator is introduced that incorporates adaptive coupling gains to govern the information exchange between the sensor nodes under event-triggering mechanism. The aim of this paper is to provide a scalable structure for unknown parameter identification independent of sensor networks' complexity. The boundedness of estimation error is ensured in the framework of uniformly ultimately bounded stability by developing an algebraic connectivity based criterion. The estimator gains including proposed coupling gains are then presented as solution to matrix inequalities. Finally, two simulation examples are presented to demonstrate the effectiveness of proposed estimation architecture.

In this paper, the distributed state and parameter estimation problem is addressed for a class of discrete-time nonlinear systems subject to sensor saturations over wireless sensor networks. In this regard, a novel estimation design is proposed that involves identification of an unknown parameter under event-triggering mechanism. A sufficient condition for exponential uniform ultimate boundedness of estimation error is established using Lyapunov stability theory. The estimator gains to ensure boundedness of error are linked to the solution of inequality constraints. Finally, the effectiveness of proposed estimator is demonstrated using a simulation example.

Titanium (Ti) based alloys (e.g., Ti6Al4V) are extensively utilized in the field orthopedic and dental implant applications due to their enhanced bio-mechanical properties. Nevertheless, their resistance to corrosion requirements needs to be enhanced. Furthermore, existence of vanadium (V) and almunium (Al) elements causes cancer and alzymer respectively. Therefore, in this research Ti-Sn-Nb alloy was produced through the powder metallurgy (PM) route. Tin (Sn) and niobium (Nb) is chosen as an alloying element which replaces toxic Al and V elements. The effect Nb on the Ti–Sn–Nb alloy was studied. Three set of variations of Nb namely 5%, 7.5% & 10% were used for the improvement of properties of parent alloy. The particle dimensions of the parent alloy were analyzed through a laser particle analyzer (LPA). Morphology was studied through Scanning Electron Microscopy (SEM) and phases were determined through X-Ray Diffraction (XRD). Vicker (450SVA) tester was utilized to examine the effect on rigidity after the addition of Nb. The hardness of the alloy was decreasing and corrosion rate was increasing with an increase in Nb content. Furthermore, niobium addition enhances the ability of appetite formation when immersed in the Stimulated body fluid (SBF).

In active noise control systems, the performance of the most celebrated filtered-x-least mean square (FxLMS) adaptive algorithm is degraded in the presence of non-linearity in the secondary path. In this article, we propose a novel approach to improve the performance of FxLMS algorithm in the presence of saturation type non-linearity in the secondary path. In the proposed method, the weights of the controller are adapted by minimizing a cost function consisting of two terms. The first term is the squared instantaneous residual error while the second term is the weighted square of the difference between input and output of (estimated) saturation non-linearity. Consequently, in case the saturation has occurred, the resultant adaptive algorithm minimizes the residual error while keeping the controller output close to its saturation limit. This avoids unnecessary fluctuation of the (controller) weights due to large variation (or windup) of the controller output after the saturation has occurred. Numerical simulations are provided to verify the superiority of the reported approach as compared to existing methods under different conditions.

This brief investigates the leader-based consensus of one-sided Lipschitz (OSL) multi-agents under switching graphs and input saturation. By using the local design approach and multiple Lyapunov functions (MLFs), a novel condition for the consensus in nonlinear agents is provided by accomplishing guaranteed local stability. The notion of the average dwell time (ADT) has been applied for dealing with the switching topologies, which relaxes the classical dwell time restriction for switching instances. In contrast to the classical methods, both input saturation and switching topologies, representing a complicated and more meaningful consensus control scenario, are considered for nonlinear agents. The conservatism in existing methods for OSL agents has been overcome owing to the utilization of MLFs and ADT. Simulation results for eight mobile agents are provided to show the effectiveness of our consensus protocol.

Due to rapid growth in wireless communication technology, higher bandwidth requirement for advance telecommunication systems, capable of operating on two or higher bands with higher channel capacities and minimum distortion losses is desired. In this paper, a compact Ultra-Wideband (UWB) V-shaped monopole antenna is presented. UWB response is achieved by modifying the ground plane with Chichen Itzia inspired rectangular staircase shape. The proposed V-shaped is designed by incorporating a rectangle, and an inverted isosceles triangle using FR4 substrate. The size of the antenna is 25 mm×26 mm×1.6 mm. The proposed V-shaped monopole antenna produces bandwidth response of 3 GHz Industrial, Scientific, and Medical (ISM), Worldwide Interoperability for Microwave Access (WiMAX), (IEEE 802.11/HIPERLAN band, 5G sub 6 GHz) which with an additional square cut amplified the bandwidth response up to 8 GHz ranging from 3.1 GHz to 10.6 GHz attaining UWB defined by Federal Communications Commission (FCC) with a maximum gain of 3.83 dB. The antenna is designed in Ansys HFSS. Results for key performance parameters of the antenna are presented. The measured results are in good agreement with the simulated results. Due to flat gain, uniform group delay, omni directional radiation pattern characteristics and well-matched impedance, the proposed antenna is suitable for WiMAX, ISM and heterogeneous wireless systems.

Disruptions have a direct impact on the process downtime and efficiency pertaining to process industry. Anomalies, in any automated process, have an impeccable impact on consumer-centric values, hi...

In most of the existing approaches for neutralizing the effects of acoustic feedback in feed-forward active noise control (FF-ANC) systems, three adaptive filters have been employed. Besides the noise control and feedback neutralization filters (FBNF), a third disturbance removal filter has been exploited to obtain suitable signals for (apposite) adaptation of the other two (adaptive filters). In this paper, we develop an effective acoustic feedback neutralization method which does not require any supplementary third adaptive filter. The proposed method incorporates a probe signal with a time-varying gain and a novel variable step-size strategy for adaptation of the FBNF. During the transient state, the FBNF is excited by a large variance probe signal and a large valued step-size. This enhances the convergence rate of the FBNF. As the FF-ANC system converges, the level of probe noise is decreased to achieve good residual error attenuation performance (at steady-state). Furthermore, the step-size is also reduced to a small value to improve the steady-state performance of the acoustic FBNF. Simulations results show that the proposed two adaptive filters-based method outperforms the existing methods for broad-band reference noise sources and yields better steady-state residual error attenuation performance for narrow-band noise signals.

Named data networking (NDN) is a revolutionary approach to cater for modern and future Internet usage trends. The advancements in web services, social networks and cloud computing have shifted Internet utilization towards information delivery. Information-centric networking (ICN) enables content-awareness in the network layer and adopts name-based routing through the NDN architecture. Data delivery in NDN is receiver-driven pull-based and governed by requests (interests) sent out by the receiver. The ever-increasing share of high-volume media streams traversing the Internet due to the popularity and availability of video-streaming services can put a strain on network resources and lead to congestion. Since most congestion control techniques proposed for NDN are receiver-based and rely on the users to adjust their interest rates, a fairness scheme needs to be implemented at the intermediate network nodes to ensure that &ldquo, rogue&rdquo, users do not monopolize the available network resources. This paper proposes a fairness-based active queue management at network routers which performs per-flow interest rate shaping in order to ensure fair allocation of resources. Different congestion scenarios for both single path and multipath network topologies have been simulated to test the effectiveness of the proposed fairness scheme. Performance of the scheme is evaluated using Jain&rsquo, s fairness index as a fairness metric.

This paper considers the leader-following consensus of multiagents with one-sided Lipschitz nonlinear dynamics by considering switching topologies. For the suitable selection of the consensus control gain matrix and coupling weight, a new condition for consensus is achieved for switching communication links with a directed spanning tree in the topology by constraining the dwell time. Employing a communication restoration mechanism allows a method to be obtained for the case in which a topology violates a permanent directed spanning tree. Computationally straightforward consensus controller design conditions that are necessary and sufficient for the former conditions are also developed for both cases. These simpler conditions can be used to obtain consensus protocol gains directly through convex routines. An algorithm is also provided to solve nonlinear constraints using the cone complementary linearization approach by considering a nonlinear objective function optimization problem. A numerical simulation is provided for multiagents that demonstrates the proposed control schemes’ efficiency.

The development of the 5G mobile communication standard attempts to meet the future needs of data users. The impact of Cyber Physical Systems (CPS) is crucial in Internet of Things (IoT) and other emerging technologies. The design of medium access mechanisms for CPS such as radio resource scheduling schemes has a significant effect on network performance. Recent literature shows that limited work is available on uplink scheduling schemes, particularly in the 5G domain. Planning a network that can address the modern needs of users entails efficient CPS scheduling mechanisms such that resources are amicably distributed between users of contrasting priorities. The prime focus of this work is to design and develop an uplink radio resource scheduling framework for CPS-based future networks such as 5G. In the designed framework, scarce radio resources are sought to be distributed efficiently according to the service-based needs of users. The proposed scheduling scheme is a service aware (SA) scheduler designed for CPS in accordance with the 5G network peculiarities, intended to achieve higher throughput and reduced latency. The proposed SA scheduler supports multi-bearer traffic and is capable of providing resources in adverse channel conditions in an efficient manner. The SA scheduling mechanism&rsquo, s performance is evaluated and compared with renowned scheduling algorithms such as blind equal throughput (BET), maximum throughput (MT), and proportional fair (PF) scheduling schemes. The simulation results obtained in a cellular environment demonstrate that the SA scheduler achieves acceptable cell throughput and end-to-end delay results in all scenarios and out-performs other contemporary scheduling schemes.

This paper proposes a novel method to analyze the local stability of Lipschitz nonlinear digital filtering schemes under saturation overflow nonlinearity. Conditions for the stability analysis and robust performance estimation are provided in the form of matrix inequalities by utilizing Lyapunov theory, local saturation overflow arithmetic, and Lipschitz condition. The proposed criterion ascertains (local) asymptotic stability in the absence of perturbations. Under the effects of external interferences, a condition for the local stability, ensuring the H∞ performance objective, is developed. The proposed approach offers a less conservative and more accurate estimate of H∞ performance index than the global method by utilizing a bound on the interferences energy. Moreover, the proposed criterion, in contrast to the existing global methods, can be employed to choose an adequate word length of a digital hardware for the specified values of tolerable perturbations energy, H∞ performance index, and fixed-point resolution. It is worth mentioning that analysis approaches have not been completely reported in the literature, in which local stability criteria for nonlinear discrete-time filtering prototypes under both overflow and disturbances have been developed. A detailed stability analysis for a nonlinear recurrent neural network is performed for demonstrating the effectiveness of the proposed scheme.

This paper presents the robust nonlinear dynamic antiwindup compensator (AWC) design for nonlinear systems with parametric uncertainties and one-sided Lipschitz nonlinearities under actuator saturation. A decoupling architecture for a full-order AWC is proposed for the case of parametric uncertainties. AWC synthesis scheme is derived by employing the quadratic Lyapunov function, the notion of quadratic inner-boundedness, the one-sided Lipschitz condition, sector condition, and ${{\mathcal L}_2}$ gain minimization. An algorithm, based on the convex routines, by employing the cone complementary linearization, recursive computation, and a bilinear term resolving approach is provided for obtaining the AWC parameters. In contrast to the existing nonlinear AWC designs, our results provide a remedy to the input saturation for a widespread class of nonlinear systems and can effectively deal with the parametric uncertainties. The suggested AWC methodology is employed to compensate windup in the buck–boost converter and one-link flexible robot with revolute joint.

This brief provides a novel criterion for the analysis of convergence of states of an infinite impulse response (IIR) digital filter to a bounded region under the influence of composite effects of quantization and overflow nonlinearities. The developed criterion is less conservative in its approach in terms of analyzing stability than conventional methods and can be employed for implementation of an IIR filter on comparatively smaller hardware word-length than existing methods. The conventional approaches consider asymptotic stability of a filter with respect to the quantization noise; however, quantization in digital filters can result into bounded oscillation and lead to infeasibility of the asymptotic stability. Therefore, a less conservative stability analysis together with estimation of steady-state region of convergence for an IIR filter is provided. In addition, the conventional approaches, analyzing stability, and steady-state region of convergence, may not guarantee an overflow oscillation-free realization of a filter. Consequently, a condition for estimating the steady-state region of convergence (along with the filter stability) with an additional constraint that the filter’s state should not overflow in the bounded region has been derived. A comparative analysis with conventional methods is provided in simulation results.

In this research an algorithm is proposed to find the total number of agents participating in a multi agent network. Also to achieve hasten distributed average consensus in order to consider a network with reliable and unreliable communication links. Class of algorithm is considered in which fixed initial state values are assigned to all agents in the network, with the iterations they updates their initial values by communicating with their neighboring agents within a multi agent network. Algorithm with weighted matrix satisfy the convergence condition of average consensus and accelerate the method to achieve the consensus. Usually this convergence process is relatively sluggish and take moreover numerous iterations to achieve a consensus. To overcome the above issues, a new approach is proposed in order to minimize the rate of convergence. A two step algorithm has been proposed, where in step one each agent employs a linear predictor to predict future agent values. In second step the computed values are used to proceed further by the other agents to achieve consensus in order to bypass the redundant states. In the end proposed algorithm is compared with other existing consensus frameworks to strengthen the claim regarding the proposed two step algorithm which leads to escalate the rate of convergence and reduces the number of iterations.

The purpose of this paper is to examine stability and originate stability criteria for nonlinear digital systems under the influence of saturation overflow, both in the absence and presence of external interference. The developed approaches can be employed to analyse overflow oscillation-free implementation of a nonlinear digital system under saturation overflow nonlinearity, caused by the finite word-length limitation of a digital hardware, such as computer processor or micro-controller. Asymptotic stability is examined in the absence of disturbance, whereas in the presence of external interference, the form of stability ensured is uniformly ultimately bounded stability, in which the states trajectories converge to an ellipsoidal region around the origin. In most of the studies reported so far, the authors have performed the overflow stability analysis of linear systems but very little (if any) work has been reported on the overflow oscillation elimination (for nonlinear systems). In the present work, sector conditions derived from saturation constraint along with Lipschitz condition are used with a suitable Lyapunov function for the stability analysis of nonlinear digital systems under overflow. The validity and efficacy of these criteria are tested by using examples from real nonlinear physical systems, including Moon chaotic system’s observer and recurrent neural network.

This study addresses the control of locally Lipschitz non-linear systems under quantisation and input saturation non-linearities. The non-linear dynamics of the systems are taken to be locally Lipschitz, rather than the conventional globally Lipschitz counterpart, to consider a generalised form of the Lipschitz non-linear systems. An ellipsoidal region containing the origin is constructed, for which the non-linear dynamics satisfy the Lipschitz condition in contrast to the conventional approaches. Saturation and quantisation non-linearities are dealt using a generalised local sector condition and a bound on the quantisation noise. A regional control strategy for the stabilisation of non-linear systems using state feedback is devised by employing these conditions, which is further extended to attain robustness against external perturbations. The proposed control strategies guarantee convergence of the states of a non-linear system inside a bounded reducible region in the neighbourhood of the origin. In contrast to the conventional approaches, the present study considers ellipsoidally Lipschitz non-linear systems, supports various types of quantisers, ensures attenuation of the disturbances, and provides a clear picture of the region of stability. An example of the application of the proposed control strategies for a modified Chua's circuit is demonstrated.

This brief focuses on the local stability analysis of 1-D digital filters that are subject to the saturation overflow nonlinearity and external interference by exploiting local saturation arithmetic. A novel stability criterion that analyzes the local asymptotic stability of a digital filter under zero external interference is investigated. Furthermore, an extension to attain a local ${H}_{\infty}$ performance is developed to tackle the external interference. The conventional global stability criteria using the global saturation arithmetic can be derived as specific cases of the proposed local results. The proposed local stability criteria provide a lesser conservative estimate of interference attenuation level in comparison with existing global techniques. Furthermore, information on the tolerable energy bound on external interference for a given attenuation level is also revealed contrary to global schemes. In addition to this, the proposed methodology can be applied to evaluate the minimum word length to achieve the desired fixed-point resolution and the performance specifications for the sake of hardware optimization. A novel two-step approach is also provided for solving the filter stability analysis condition using convex routines. A numerical example is presented to demonstrate these features.

Here, in this manuscript, we studied the structural, electronic, and thermoelectric properties of Pb doped thallium antimony telluride crystal structure both experimentally and theoretically. Lead (Pb) doped thallium antimony telluride with different concentration (x) have been prepared by solid state reaction method and Ball milling technique. X-Ray Diffraction reveals that the crystal structure of Tl8.33Sb1.67−xPbxTe6 nano-structured compounds are iso-structural with Tl4SbTe3 compound. We showed that increasing the Pb concentrations results in an increase of the electrical conductivity and Seebeck coefficient, and is also confirmed by Density-Functional Theory (DFT) calculations. The power factor (PF = S2σ) enhanced by a larger factor as compared to the enhancement of the electronic thermal conductivity that was achieved simultaneously through Pb doping in thallium antimony telluride nano-compounds. This significantly increases the ratio of PF/κ that results in an enormously enhanced figure-of-merit (ZT) value from 0.19 to 0.46 at T = 560 K. DFT calculations also show the enhancement in S due to the reduction in density of states (DOS) at Fermi energy. The highest ZT = 0.46(0.22) was recorded for Pb doped thallium antimony telluride compound experimentally (theoretically). These results indicate a route to harness the thermoelectric properties of thallium antimony telluride based materials for electronic and thermoelectric applications.

Genetic algorithm (GA)-based direction of arrival (DOA) estimation is proposed using fourth-order cumulants (FOC) and ESPRIT principle which results in Multiple Invariance Cumulant ESPRIT algorithm. In the existing FOC ESPRIT formulations, only one invariance is utilised to estimate DOAs. The unused multiple invariances (MIs) must be exploited simultaneously in order to improve the estimation accuracy. In this paper, a fitness function based on a carefully designed cumulant matrix is developed which incorporates MIs present in the sensor array. Better DOA estimation can be achieved by minimising this fitness function. Moreover, the effectiveness of Newton’s method as well as GA for this optimisation problem has been illustrated. Simulation results show that the proposed algorithm provides improved estimation accuracy compared to existing algorithms, especially in the case of low SNR, less number of snapshots, closely spaced sources and high signal and noise correlation. Moreover, it is observed th...

This paper proposes a novel linear matrix inequality (LMI)-based stability criterion to avoid overflow oscillations in 2-D digital filters described by a Roesser state-space model with saturation-type overflow characteristics. In contrast to the conventional approaches, the proposed overflow oscillation elimination methodology can be applied to linear parameter varying time-variant digital filters under overflow subject to both state and output disturbances. For such filters, the proposed criterion ensures the zero-input overflow stability as well as robustness against interferences with a guaranteed H ∞ performance bound. A numerical example is presented to demonstrate the effectiveness of the proposed approach. HighlightsOverflow elimination analysis for time-varying 2-D digital filters of Roesser type.Inaugural treatment of LPV approach for stability analysis of 2-D digital filters.Robust stability criterion is developed for dealing with external interferences.External interferences are considered both in state and output equations.Numerical example is provided for a 2-D filter with three parametric variations performance condition, for dealing with the external interferences.

Artificial Intelligence (AI) and Machine Learning (ML) are envisaged to play key roles in 5G networks. Efficient radio resource management is of paramount importance for network operators. With the advent of newer technologies, infrastructure, and plans, spending significant radio resources on estimating channel conditions in mobile networks poses a challenge. Automating the process of predicting channel conditions can efficiently utilize resources. To this point, we propose an ML-based technique, i.e., an Artificial Neural Network (ANN) for predicting SINR (Signal-to-Interference-and-Noise-Ratio) in order to mitigate the radio resource usage in mobile networks. Radio resource scheduling is generally achieved on the basis of estimated channel conditions, i.e., SINR with the help of Sounding Reference Signals (SRS). The proposed Non-Linear Auto Regressive External/Exogenous (NARX)-based ANN aims to minimize the rate of sending SRS and achieves an accuracy of R = 0.87. This can lead to vacating up to 4% of the spectrum, improving bandwidth efficiency and decreasing uplink power consumption.

This paper describes the anti-windup compensator (AWC) design methodologies for stable and unstable cascade plants with cascade controllers facing actuator saturation. Two novel full-order decoupling AWC architectures, based on equivalence of the overall closed-loop system, are developed to deal with windup effects. The decoupled architectures have been developed, to formulate the AWC synthesis problem, by assuring equivalence of the coupled and the decoupled architectures, instead of using an analogy, for cascade control systems. A comparison of both AWC architectures from application point of view is provided to consolidate their utilities. Mainly, one of the architecture is better in terms of computational complexity for implementation, while the other is suitable for unstable cascade systems. On the basis of the architectures for cascade systems facing stability and performance degradation problems in the event of actuator saturation, the global AWC design methodologies utilizing linear matrix inequalities (LMIs) are developed. These LMIs are synthesized by application of the Lyapunov theory, the global sector condition and the ℒ 2 gain reduction of the uncertain decoupled nonlinear component of the decoupled architecture. Further, an LMI-based local AWC design methodology is derived by utilizing a local sector condition by means of a quadratic Lyapunov function to resolve the windup problem for unstable cascade plants under saturation. To demonstrate effectiveness of the proposed AWC schemes, an underactuated mechanical system, the ball-and-beam system, is considered, and details of the simulation and practical implementation results are described.

In this paper, we propose a 3-dimensional modified unitary matrix pencil (3D MUMP) method for simultaneous estimation of azimuth and elevation angles along with the frequencies of multiple plane wave signals. The unitary transformation is utilized in the 3-dimensional matrix pencil (3D MP) method in order to reduce the computational complexity since it very efficiently converts complex computations into real ones. The proposed method can be considered as an extension to the existing 2-dimensional unitary matrix pencil (2D UMP) method with the following advantages. First, the computationally expensive grouping algorithm is avoided by exploiting the similar eigen-structure property of the matrices (in 3D UMP method) whose eigenvalues yield the required 3D poles. Furthermore, the possibility of wrong groupings is also reduced significantly. Some simulation results are presented at the end to compare the performance of the proposed method with the existing methods.

In this paper, we propose a new 2-dimensional beamspace matrix pencil (2D BMP) method for direction of arrival (DOA) estimation of plane wave signals using a uniform rectangular array (URA). Based on some a priori information about DOA, the proposed method transforms the complex signal subspace in 2D matrix pencil (2D MP) method [Y. Hua, Estimating two-dimensional frequencies by matrix enhancement and matrix pencil, IEEE Trans. Signal Process. 40 (9) (1992) 2267-2280] into a real and reduced dimensional beamspace using the discrete Fourier transform (DFT) matrix transformation. Consequently, the computational complexity is reduced (several times) in comparison with 2D MP method. Computer simulations are provided to show that 2D BMP method gives comparable performance in terms of average mean square error of the estimated DOA with lesser floating point operations as compared to the existing (MP) methods.

This letter proposes a method for active noise control (ANC) systems with online acoustic feedback neutralization. The proposed method is a modified version of authors' previous work, and the objective here is to reduce the computational complexity. This is achieved by combining the role of feedback path modeling and neutralization filters. The computer simulations are carried out which demonstrate that the proposed method achieves better performance than the existing methods and at somewhat reduced computational cost.

In this paper, we propose to employ an extension to the natural gradient algorithm for robust Independent Component Analysis against outliers. The standard natural gradient algorithm does not exhibit this property since it employs nonrobust sample estimates for computing higher order moments. In order to overcome this drawback, we propose to use robust alternatives to higher order moments, which are comparatively less sensitive to outliers in the observed data. Some computer simulations are presented to show that the proposed method, as compared to the standard natural gradient algorithm, gives better performance in the presence of outlying data.

In this paper, we propose to employ a characteristic function based non-Gaussianity measure as a one-unit contrast function for independent component analysis. This non-Gaussianity measure is a weighted distance between the characteristic function of a random variable and a Gaussian characteristic function at some adequately chosen sample points. Independent component analysis of an observed random vector is performed by optimizing the above mentioned contrast function (for different units) using a fixed-point algorithm. Moreover, in order to obtain a better separation performance, we employ a mechanism to choose appropriate sample points from an initially selected sample vector. Finally, some computer simulations are presented to demonstrate the validity and effectiveness of the proposed method.