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Copious research has been conducted on Capacitive Pressure Sensors over the decades with a focus on Silicon being the primary filming element. However, due to Silicon Carbide emerging as superior in harsh environmental conditions, the research is gravitating towards it for industrial applications. This work presents a new analytical model for a polycrystalline silicon carbide-based capacitive pressure sensor working in touch-mode operation. Carbide demonstrates properties like electrical stability, mechanical robustness and chemical inertness which puts it on the frontier of research. The mathematical model proposed is a simple yet powerful tool in manipulating design and sizing for fast analysis. It is quicker and bypasses the need for complex simulation software. The analysis is purely mathematical and hence the results are analyzed with MATLAB. The mathematical model developed is verified with a standard Finite Element Analysis (FEM) using COMSOL v5.2. The results of the mathematical analysis dovetail well with the FEM analysis and show a significant improvement in both the sensitivity and capacitance generated. [ABSTRACT FROM AUTHOR]

Parameter estimation of chaotic systems is an important problem in nonlinear science and has aroused increasing interest of many research fields, which can be basically reduced to a multidimensional optimization problem. In this paper, an improved boundary bird swarm algorithm is used to estimate the parameters of chaotic systems. This algorithm can combine the good global convergence and robustness of the bird swarm algorithm and the exploitation capability of improved boundary learning strategy. Experiments are conducted on the Lorenz system and the coupling motor system. Numerical simulation results reveal the effectiveness and with desirable performance of IBBSA for parameter estimation of chaotic systems. [ABSTRACT FROM AUTHOR]

The existing Block Compressive Sensing (BCS) based image ciphers adopted the same sampling rate for all the blocks, which may lead to the desirable result that after subsampling, significant blocks lose some more-useful information while insignificant blocks still retain some less-useful information. Motivated by this observation, we propose a scalable encryption framework (SEF) based on BCS together with a Sobel Edge Detector and Cascade Chaotic Maps. Our work is firstly dedicated to the design of two new fusion techniques, chaos-based structurally random matrices and chaos-based random convolution and subsampling. The basic idea is to divide an image into some blocks with an equal size and then diagnose their respective significance with the help of the Sobel Edge Detector. For significant block encryption, chaos-based structurally random matrix is applied to significant blocks whereas chaos-based random convolution and subsampling are responsible for the remaining insignificant ones. In comparison with the BCS based image ciphers, the SEF takes lightweight subsampling and severe sensitivity encryption for the significant blocks and severe subsampling and lightweight robustness encryption for the insignificant ones in parallel, thus better protecting significant image regions. [ABSTRACT FROM AUTHOR]

In mobile ad hoc networks (MANETs), link failures are caused frequently because of node's mobility and use of unreliable wireless channels for data transmission. Multipath routing strategy can cope with the problem of the traffic overloads while balancing the network resource consumption. In the paper, an optimized node-disjoint multipath routing (ONMR) protocol based on ad hoc on-demand vector (AODV) is proposed to establish effective multipath to enhance the network reliability and robustness. The scheme combines the characteristics of reverse AODV (R-AODV) strategy and on-demand node-disjoint multipath routing protocol to determine available node-disjoint routes with minimum routing control overhead. Meanwhile, it adds the backup routing strategy to make the process of data salvation more efficient in case of link failure. The results obtained through various simulations show the effectiveness of the proposed scheme in terms of route availability, control overhead and packet delivery ratio. [ABSTRACT FROM AUTHOR]

In the modern society, most networked critical infrastructures are coupled together and can be modeled as interconnected networks. Cascading failures caused by overload in interconnected networks are extremely complicated and still lack of corresponding researches. It is crucial to explore a systematic design and load management method for complex interconnected network. In this paper, a probabilistic heterogeneous capacity allocation model and a preventive load redistribution model are firstly proposed. Based on the novel models failure cascades in interconnected networks are studied in detail. Numerical simulations and analysis results show that robustness of interconnected network depends on the network topology, capacity allocation pattern and load management strategy. The novel models have guiding significance for the design and optimal management of robust interconnected infrastructure networks. [ABSTRACT FROM AUTHOR]

During last decades, Cellular Automata (CAs) as bio-inspired parallel computational tools have been proven rather efficient and robust on modeling and simulating many different physical processes and systems and solving scientific problems, in which global behavior arises from the collective effect of simple components that interact locally. Among others of most renowned and well established CA applications, crowd evacuation and pedestrian dynamics are considered ones of the most timely and lively topics. Numerous models and computational paradigms of CAs either as standalone models or coupled with other theoretical and practical modeling approaches have been introduced in literature. All these crowd models are taking advantage of the fact that CA show evidence of a macroscopic nature with microscopic extensions, i.e. they provide adequate details in the description of human behavior and interaction, whilst they retain the computational cost at low levels. In this aspect, several CA models for crowd evacuation focusing on different modeling principles, like potential fields techniques, obstacle avoidance, follow the leader principles, grouping and queuing theory, long memory effects, etc. are presented in this paper. Moreover, having in mind the inherent parallelism of CA and their straightforward implementation in hardware, some anticipative crowd management systems based on CAs are also shown when operating on medium density crowd evacuation for indoor and outdoor environments. Real world cases and different environments were examined proving the efficiency of the proposed CA based anticipative systems. The proposed hardware implementation of the CAs-based crowd simulation models is advantageous in terms of low-cost, high-speed, compactness and portability features. Finally, robot guided evacuation with the help of CAs is also presented. The proposed framework relies on the well established CAs simulation models, while it employs a real-world evacuation implementation assisted by a mobile robotic guide, which in turn guides people towards a less congestive exit at a time. [ABSTRACT FROM AUTHOR]

In this paper, we consider the nonlinear orbit tracking control of rotating multi-tethered satellite formations in Halo orbits. A dynamical formulation is first applied for a rotating multi-tethered formation arranged in a hub-spoke configuration. Then, a new nonlinear optimal tracking control method is proposed for the stabilization of the parent satellite to follow the predefined trajectory. Numerical simulations illustrating the effectiveness of the nonlinear controller are presented. The results show that the actual trajectory of the parent satellite tracks the nominal Halo orbit with good accuracy under the influence of initial injection errors and the perturbations of subsatellites. In addition, the control acceleration and the total fuel cost of the control can be quite reasonable. Furthermore, a number of the relevant parameters that affect the control costs are varied in order to demonstrate the robustness of the nonlinear controller. [ABSTRACT FROM AUTHOR]

Most of modern systems are coupled by two sub-networks and therefore should be modeled as interdependent networks. The study towards robustness of interdependent networks becomes interesting and significant. In this paper, mainly by numerical simulations, the robustness of interdependent Erdös-Rényi (ER) networks and interdependent scale-Free (SF) networks coupled by two sub-networks with different average degree are investigated. First, we study the robustness of interdependent networks under random attack. Second, we study the robustness of interdependent networks under targeted attack on high or low degree nodes, and find that interdependent networks with different average degree are significantly different from those interdependent networks with equal average degree. [ABSTRACT FROM AUTHOR]

Inspired by quantum theory and reinforcement learning, a new framework of learning in unknown probabilistic environment is proposed. Several simulated experiments are given; the results demonstrate the robustness of the new algorithm for some complex problems. Also we generalized the Grover algorithm to improve the rate of converging to an optimal path. In other words, the new generalized algorithm helps to increase the probability of selecting good actions with better weights' adjustments. [ABSTRACT FROM AUTHOR]

Process and supply variations all have a large influence on current-mode signaling (CMS) circuits, limiting their application on the fields of high-speed low power communication over long on-chip interconnects. A variation-insensitive CMS scheme (CMS-Bias) was offered, employing a particular bias circuit to compensate the effects of variations, and was robust enough against inter-die and intra-die variations. In this paper, we studied in detail the principle of variation tolerance of the CMS circuit and proposed a more suitable bias circuit for it. The CMS-Bias with the proposed bias circuit (CMS-Proposed) can acquire the same variation tolerance but consume less energy, compared with CMS-Bias with the original bias circuit (CMS-Original). Both the CMS schemes were fabricated in 180 nm CMOS technology. Simulation and measured results indicate that the two CMS interconnect circuits have the similar signal propagation delay when driving signal over a 10 mm line, but the CMS-Proposed offers about 9% reduction in energy/bit and 7.2% reduction in energy-delay-product (EDP) over the CMS-Original. Simulation results show that the two CMS schemes only change about 5% in delay when suffering intra-die variations, and have the same robustness against inter-die variations. Both simulation and measurements all show that the proposed bias circuits, employing self-biasing structure, contribute to robustness against supply variations to some extent. Jitter analysis presents the two CMS schemes have the same noise performance. [ABSTRACT FROM AUTHOR]

This paper deals with the finite-time chaos synchronization of a new hyperchaotic Lorenz system. Based on the finite-time stability theory, a simple and robust controller is proposed to realize finite-time chaos synchronization for the hyperchaotic Lorenz system. Theoretical analysis proved that the scheme can ensure the error system globally finite-time stable. Numerical simulations are provided to show the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

A two-loop control has been designed for a boost converter. An internal sliding-mode control loop forces the converter inductor current to track the reference established by H∞ control of the output voltage in an outer loop. The outer H∞ controller is designed through loop shaping concepts. A practical design approach that aims at systematizing the procedure for the selection of inner sliding mode control parameters is also presented. The closed loop characteristics of a typical low-power boost converter with the proposed dual loop controller implemented in the actual switched model is validated through computer simulation. The proposed controller is found to be superior due to its low distortion property, good regulating performance and insensitivity to load variations. Finally, the validity and effectiveness of the control schemes are verified through hardware experiments. [ABSTRACT FROM AUTHOR]

In this work we have used computer models of social-like networks to show by extensive numerical simulations that cooperation in evolutionary games can emerge and be stable on this class of networks. The amounts of cooperation reached are at least as much as in scale-free networks but here the population model is more realistic. Cooperation is robust with respect to different strategy update rules, population dynamics, and payoff computation. Only when straight average payoff is used or there is high strategy or network noise does cooperation decrease in all games and disappear in the Prisoner's Dilemma. [ABSTRACT FROM AUTHOR]

There are different kinds of multiple classifiers in complex recognition systems in pursuit of better recognition capabilities. To exploit the classifiers' potential as individual ones sufficiently and enable them to work cooperatively for the best classification results, they need to be considered as a whole and be dynamically managed according to the changing recognition occasions. In this paper, we present the conception of distributed Multiple Classifiers Management (MCM) and a self-adaptive recursive MCM model based on Mixture-of-Experts (ME). A control subsystem is consisted in the model, which allows the classification progress to be controlled by the systems' priori information when necessary. The model adjusts its parameters dynamically according to the current recognition state and gives the recognition results by combining the current individual classifiers' results with the previous combination result under priori information's control. An algorithm based on one step error correction is presented to acquire the model's parameters dynamically. It takes the previous times' ensemble classification results as true and corrects the current weights of the classifiers. At last, an experiment on the recognition of space objects is simulated. The experiment results show that the MCM model in this paper is effective for complex recognition system containing heterogeneous classifiers on improving the recognition rate and robustness. [ABSTRACT FROM AUTHOR]

The analysis of delay dynamics (DD) is the basic big picture in networked control systems (NCS) research since the knowledge of its behavior may improve the design of more robust controllers, and consequently, the system performance. However, the extreme complexity of modern communications and networks, coupled with their traffic characteristics, makes the characterization of their performance through analytical models a difficult task. Relying on fractional calculus (FC), this paper studies the dynamics of IP delays and attempts to clarify the most important features of network traffic, providing the reader some connections between traffic in communication networks and FC. Likewise, a fractional order model of DD is presented based on a survey of current network traffic models. Some simulations are given to validate the proposed model. [ABSTRACT FROM AUTHOR]

Corrosion is a common phenomenon and critical aspects of steel structural application. It affects the daily design, inspection, and maintenance in structural engineering, especially for the heavy and complex industrial applications, where the steel structures are subjected to hash corrosive environments in combination of high working stress condition and often in open field and/or under high temperature production environments. In the paper, it presents the actual engineering application of advanced finite element methods in the predication of the structural integrity and robustness at a designed service life for the furnaces of alumina production, which was operated in the high temperature, corrosive environments, and rotating with high working stress condition. [ABSTRACT FROM AUTHOR]

oActive sliding mode control is one of the effective methods to synchronize chaotic systems in the presence of uncertainties. Use of the method, however, requires decision making on how to choose the control parameters for a specific performance. In this paper we propose an algorithm to determine the best control parameters for which the minimum control efforts are required to synchronize two identical or non-identical chaotic systems. We have also determined the maximum range of the uncertainties on which the selected control parameters to work properly. The effectiveness of the proposed method has been verified through numerical simulations. [ABSTRACT FROM AUTHOR]

The problem of computing a d-dimensional Euclidean Voronoi diagram of spheres is relevant to many areas, including computer simulation, motion planning, CAD, and computer graphics. This paper presents a new algorithm based on the explicit computation of the coordinates and radii of Euclidean Voronoi diagram vertices for a set of spheres. The algorithm is further applied to compute the Voronoi diagram with a specified precision in a fixed length floating-point arithmetic. The algorithm is implemented using the ECLibrary (Exact Computation Library) and tested on the example of a 3-dimensional Voronoi diagram of a set of spheres. [ABSTRACT FROM AUTHOR]

The stabilization of nonlinear systems that exhibit chaotic behavior is presented using notch-filter output feedback control. The effect of constant disturbance input and/or parametric uncertainty on the systems' performance is studied for a class of nonlinear systems where bifurcation analysis is used to illustrate the period-doubling route to chaos. The motivation for using the notch-filter in the feedback is to selectively damp-out portions of the closed-loop power spectrum, thus truncating period-doubling. Double-notch-filter feedback is introduced as a regulation scheme to bring the chaotic system to a steady state. The effect of using the fixed-parameters feedback on the equilibrium points is carefully studied, and a robust numerical parameter-tuning method is presented. The efficiency of this method is verified via simulations applied to a third-order uncertain nonlinear system that has typical applications in power generation and voltage control. A comparative study with a model-based recursive backstepping controller is carried out to highlight the advantages and limitations of the proposed control system. [ABSTRACT FROM AUTHOR]

This paper addresses the adaptive synchronization problem of a class of different uncertain chaotic systems. A general adaptive robust controller and parameters update rule are designed. It is proved theoretically that the controller and update rule can make the drive-response systems with different structures asymptotically synchronized, and change the unknown parameters to constants when noise exists. When the drive system is certain, the unknown parameters of the response system can be updated to the predicted values. The results of numerical simulations show the effectiveness of the adaptive controller. [ABSTRACT FROM AUTHOR]

This study addresses the adaptive synchronization of a class of uncertain chaotic systems in the drive-response framework. For a class of uncertain chaotic systems with parameter mismatch and external disturbances, a robust adaptive observer based on the response system is constructed to practically synchronize the uncertain drive chaotic system. Lyapunov stability theory ensures the practical synchronization between the drive and response systems even if Lipschitz constants on function matrices and bounds on uncertainties are unknown. Numerical simulation of two illustrative examples are given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, the sparse approximate inverse (SAI) preconditioning method is applied to a single SMP node of the Earth Simulator (ES) using OpenMP. The developed method is tested for applications with contact conditions, and demonstrates efficiency and robustness for a wide range of problem sizes. The efficiency and robustness of the SAI preconditioner is competitive with that of the selective blocking method, which is a special preconditioning method for contact problems. The developed method is ported to Hitachi SR8000 and IBM SP-3, and the performance and robustness is evaluated. [ABSTRACT FROM AUTHOR]

Recent advances in complex network research have stimulated increasing interests in understanding the relationship between the topology and dynamics of complex networks. Based on the theory of complex networks and computer simulation, we analyze the robustness to time-delay in linear consensus problem with different network topologies, such as global coupled network, star network, nearest-neighbor coupled network, small-world network, and scale-free network. It is found that global coupled network, star network, and scale-free network are vulnerable to time-delay, while nearest-neighbor coupled network and small-world network are robust to time-delay. And it is found that the maximum node degree of the network is a good predictor for time-delay robustness. And it is found that the robustness to time-delay can be improved significantly by a decoupling process to a small part of edges in scale-free network. [ABSTRACT FROM AUTHOR]

We investigate the performances of collective task-solving capabilities and the robustness of complex networks of automata using the density and synchronization problems as typical cases. We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to several kinds of scale-free graphs. In addition, we show that Watts–Strogatz networks are as robust in the face of random perturbations, both transient and permanent, as configuration scale-free networks, while being widely superior to Barabási–Albert networks. This result differs from information diffusion on scale-free networks, where random faults are highly tolerated by similar topologies. [ABSTRACT FROM AUTHOR]

In this paper we investigate several methods for controlling chaos in Aihara's chaotic neuron model. We first discuss the stability of exponential feedback control method for this model. To obviate predetermining the unstable periodic orbits of the system, two other methods are developed. We analyze why the conventional delayed feedback control method cannot be employed here, and then give a modified form for recursive delayed feedback control and apply it to control chaos in this model. To obtain high-periodic orbits more easily, a delayed exponential feedback control method is proposed, by which we can obtain different periodic orbits by changing parameters. Computer simulations show good control effects and robustness against noise. [ABSTRACT FROM AUTHOR]