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In this paper, a mixed event-triggered and continuous-time control method is proposed, which can guarantee finite-time stabilisation of the fixed point in a class of time-varying nonlinear systems. Benefiting from an event-triggered framework, which is constructed based on the indefinite Lyapunov theory, the communication/computation costs in the transient time can be reduced by using the proposed method. In a special case, this method is converted to a fully event-triggered control strategy for asymptotic stabilisation of the fixed point in the considered class of time-varying nonlinear systems. The effectiveness of the proposed method is verified by numerical simulations. © 2021 Informa UK... 

In this paper, a mixed event-triggered and continuous-time control method is proposed, which can guarantee finite-time stabilisation of the fixed point in a class of time-varying nonlinear systems. Benefiting from an event-triggered framework, which is constructed based on the indefinite Lyapunov theory, the communication/computation costs in the transient time can be reduced by using the proposed method. In a special case, this method is converted to a fully event-triggered control strategy for asymptotic stabilisation of the fixed point in the considered class of time-varying nonlinear systems. The effectiveness of the proposed method is verified by numerical simulations. © 2021 Informa UK... 

This paper is concerned with the tele-operation of autonomous vehicles over analog Additive White Gaussian Noise (AWGN) channel, which is subject to transmission noise and power constraint. The nonlinear dynamic of autonomous vehicles is described by the unicycle model and is cascaded with a bandpass filter acting as encoder. Using the describing function method, the nonlinear dynamic of autonomous vehicles is represented by an approximate linear system. Then, the available results for linear control over analog AWGN channel are extended to account for linear continuous time systems with non-real valued and multiple real valued eigenvalues and for tracking a non-zero reference signal.... 

In this study, a novel three-dimensional continuous-time integrated guidance and control (IGC) scheme is presented. The proposed method is developed on the basis of generalized model predictive control (GMPC) approach and super-twisting extended state observer (STESO). The GMPC is used to generate the optimal closed form control law for the interceptor and the STESO is applied to estimate the maneuvering target lateral accelerations as well as the lumped disturbances. To the aim of IGC design, a six-degrees-of-freedom model based on the interceptor-target kinematics and interceptor dynamics is constructed. Afterward, the GMPC control law formulation for a nonlinear system exposed to... 

Chaos control of a spinning disk having transverse vibration is considered in this article by stabilizing the system on its corresponding unstable periodic orbit (UPO). At the first step, the system continuous-time dynamic equations are quantized by utilizing a proper Poincare map. Then, using the regression method a linear description from the obtained cross points is achieved around the corresponding fixed point of the target UPO. Finally, through solving the Riccati equation, an optimal controller is introduced which stabilizes the system on its unstable fixed point. At the end, the effectiveness of the proposed control method is examined through numerical simulations. © SAGE Publications... 

The quality of an architectural design of a software system has a great influence on achieving non-functional requirements of a system. A regular software development project is often influenced by non-functional factors such as the customers' expectations about the performance and reliability of the software as well as the reduction of underlying risks. The evaluation of non- functional parameters of a software system at the early stages of design and its development process are often considered as major factors in dealing with these issues. Because these evaluations can help us to choose the most proper model which is the securest and the most reliable.In this paper, a method is presented... 

Importance measures are integral parts of risk assessment for risk-informed decision making. Because the parameters of a risk model, such as the component failure rates, are functions of time and a perturbation (change) in their values can occur during the mission time, time dependence must be considered in the evaluation of the importance measures. In this paper, it is shown that the change in system performance at time t, and consequently the importance of the parameters at time t, depends on the parameters perturbation time and their value functions during the system mission time. We consider a nonhomogeneous continuous time Markov model of a series-parallel system to propose the... 

In cloud computing services, high availability is one of the quality of service requirements which is necessary to maintain customer confidence. High availability systems can be built by applying redundant nodes and multiple clusters in order to cope with software and hardware failures. Due to cloud computing complexity, dependability analysis of the cloud may require combining state-based and nonstate-based modeling techniques. This article proposes a hierarchical model combining reliability block diagrams and continuous time Markov chains to evaluate the availability of OpenStack private clouds, by considering different scenarios. The steady-state availability, downtime, and cost are used... 

In the present work, multiple non existing model order reduction (MOR) techniques for unstable second-order form systems (SOSs) are proposed. For unstable SOSs, continuous-time algebraic Lyapunov equations get unsolvable that halt the reduction process. To avoid this problem, unstable SOS is first decomposed into stable and unstable portions and balanced truncation is applied to the stable part. The obtained reduced order model (ROM) for the stable portion is augmented with the unstable portion to obtain the overall reduced system. It is observed that the second-order structure in ROM for the first technique gets lost as well as augmented unstable dynamics degrade the ROM performance. To... 

In the present work, multiple non existing model order reduction (MOR) techniques for unstable second-order form systems (SOSs) are proposed. For unstable SOSs, continuous-time algebraic Lyapunov equations get unsolvable that halt the reduction process. To avoid this problem, unstable SOS is first decomposed into stable and unstable portions and balanced truncation is applied to the stable part. The obtained reduced order model (ROM) for the stable portion is augmented with the unstable portion to obtain the overall reduced system. It is observed that the second-order structure in ROM for the first technique gets lost as well as augmented unstable dynamics degrade the ROM performance. To... 

In this paper, an attractive and novel algorithm for improving irreducible model identification of continuous time(CT) MIMO systems has been presented. The algorithm is based on least - squares (LS) estimates of Markov parameters (MP) using input output data and residual whitening. By choosing a linear-in-parameters model structure, the estimation becomes linear and asymptotically robust to zero-mean additive disturbances. CT Markov parameters may result in diverging approximations even for stable systems. To remove the existing limitations in the case of systems with low or zero damping, Markov Poisson parameters have been used to lend much flexibility to the estimation model. The MIMO... 

Simulation of large-scale nonlinear dynamical systems on hardware with a high resemblance to their mathematical equivalents has been always a challenge in engineering. This paper presents a novel current-input current-output circuit supporting a systematic synthesis procedure of log-domain circuits capable of computing bilateral dynamical systems with considerably low power consumption and acceptable precision. Here, the application of the method is demonstrated by synthesizing four different case studies: 1) a relatively complex 2-D nonlinear neuron model; 2) a chaotic 3-D nonlinear dynamical system Lorenz attractor having arbitrary solutions for certain parameters; 3) a 2-D nonlinear Hopf... 

Millimeter-wave radars are essential for automotive sensing, medical imaging, and safety- monitoring applications. Among different architectures, frequency-modulated continuous-wave (FMCW) radars are particularly suited for miniature integration targeting portable consumer applications with detection ranges up to a few tens of meters. This translates to a relatively low requirement of transmitter (TX) output peak power and hence is well suited for implementation using low-supply-voltage CMOS processes. To avoid saturating the receiver (RX) under CW operation, FMCW radars must achieve high TX-to-RX isolation in the front-end. Typically, at least 40dB of isolation is necessary for W-band (75... 

In this paper, we consider a multiple-input single-output (MISO) linear time-varying system whose output is a superposition of scaled and time-frequency shifted versions of inputs. The goal of this paper is to determine system characteristics and input signals from the single output signal. More precisely, we want to recover the continuous time-frequency shift pairs, the corresponding (complex-valued) amplitudes and the input signals from only one output vector. This problem arises in a variety of applications such as radar imaging, microscopy, channel estimation and localization problems. While this problem is naturally ill-posed, by constraining the unknown input waveforms to lie in... 

We consider a class of continuous-Time hybrid dynamical systems that correspond to subgradient flows of a piecewise linear and convex potential function with finitely many pieces, and which includes the fluid-level dynamics of the Max-Weight scheduling policy as a special case. We study the effect of an external disturbance/perturbation on the state trajectory, and establish that the magnitude of this effect can be bounded by a constant multiple of the integral of the perturbation. © 1963-2012 IEEE  

Over the last two decades, mathematical modeling has become a popular tool in study of blood coagulation. This paper describes the coagulation pathway and presents a mathematical model for the generation of blood clot in human vasculature. Parameters of interest in this study include procoagulants and anticoagulants whose activity may be enhanced by various activator enzymes. The process of human blood clotting involves a complex interaction between these parameters and continuous time and state processes. In this work, we propose to model these highly inter-relational processes by a set of nonlinear chemical rate equations. We have modeled this process as a dynamical system, as chemical... 

We investigate the problem of practical output regulation: Design a controller that brings the system output in the vicinity of a desired target value while keeping the other variables bounded. We consider uncertain systems that are possibly nonlinear and the uncertainty of the linear part is modeled element-wise through a parametric family of matrix boxes. An optimization-based design procedures is proposed that delivers a continuous-time control and estimates the maximal regulation error. We also analyze an event-triggered emulation of this controller, which can be implemented on a digital platform, along with an explicit estimates of the regulation error. IEEE  

In this paper, an attractive and novel algorithm for improving irreducible model identification of continuous time(CT) MIMO systems has been presented. The algorithm is based on least - squares (LS) estimates of Markov parameters (MP) using input output data and residual whitening. By choosing a linear-in-parameters model structure, the estimation becomes linear and asymptotically robust to zero-mean additive disturbances. CT Markov parameters may result in diverging approximations even for stable systems. To remove the existing limitations in the case of systems with low or zero damping, Markov Poisson parameters have been used to lend much flexibility to the estimation model. The MIMO... 

A switched capacitor circuit frequently appears in literature in form of sample and hold or master-slave sampling filter. We call this block Sample and Hold Master-Slave Sampling Filter (SH-MSSF). Considering the time varying nature of this circuit it is difficult to predict its behavior, though it looks like a very simple circuit. So there exists no formula describing its function in all of its applications. In this brief, we present a closed-form transfer function, explaining the operation of SH-MSSF, based on state-space analysis. Then by interpolating an infinite number of such transfer functions a continuous-time formula is derived that can exactly model the behavior of this (Linear... 

In this article, we investigate the problem of practical output regulation, i.e., to design a controller that brings the system output in the vicinity of a desired target value while keeping the other variables bounded. We consider uncertain systems that are possibly nonlinear and the uncertainty of their linear parts is modeled element wise through a parametric family of matrix boxes. An optimization-based design procedure is proposed that delivers a continuous-time control and estimates the maximal regulation error. We also analyze an event-triggered emulation of this controller, which can be implemented on a digital platform, along with an explicit estimate of the regulation error. ©...