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This paper presents a new efficient numerical method for state estimation of Markov Jump Linear Systems (MJLSs). It is based on the selection of a finite set of typical trajectories of an underlying piecewise deterministic Markov process (PDMP) related to the gain matrices of the optimal Kalman-Bucy filter and allows for pre-computations. The trajectories are optimally selected using quantization...
The approximation of linear time-invariant (LTI) systems by sampling series is a central task of signal processing. For the Paley-Wiener space PW1π of bandlimited signals with absolutely integrable Fourier transform, it is known that there exist signals and stable LTI systems such that the canonical approximation process diverges. In this paper we analyze the structure of the sets of signals and systems...
The Fredholm Integro-differential equations (IDEs) of the second kind appear in many scientific applications. Mathematical methods for the solution of the Fredholm IDEs have been developed over the last decade. In this article, we introduce a new variant of Geometric Mean iterative (MGM) method to solve the Fredholm fourth order IDEs of the second kind. As is typical with the IDEs, the problem is...
In this paper, a new adaptive control framework for linear systems in which the matched uncertainty can be linearly parameterized is introduced to guarantee the global exponential stability of reference tracking error and parameter convergence error without requiring restrictive persistent excitation condition. The framework uses time histories of control input and system signals to construct least-squares...
This talk will review the main challenges in preconditioning electromagnetic integral equations and it will delineate some future perspectives for this field. Special attention will be devoted to analyze conditioning problems and challenges in all regimes of interest for applications including the low-frequency, the high frequency, and the elliptic regime. Theoretical considerations will be matched...
This paper focuses on mesh-partitioning metrics in large-scale parallel computational fluid dynamics (CFD) simulations. Mesh partitioning has a significant influence on the efficiency of parallel preconditioned conjugated gradient (PCG) solving procedure, which is the most representative and timeconsuming part in parallel CFD. As the efficiency of parallel PCG depends on load balancing, communication...
This paper focuses on Norm-Optimal Iterative Learning Control (NO-ILC) framework for Single-Input-Single-Output (SISO) Linear Time Invariant (LTI) systems and considers the filter design problem in frequency domain. Modeling uncertainty, in general, degrades the performance of NO-ILC. Hence, ensuring Robust Monotonic Convergence (RMC) against modeling uncertainty is important, but the state-of-art...
This paper develops two proportional-type networked iterative learning control (NILC) schemes for a class of linear-time-invariant systems with stochastic packet dropout being subject to Bernoulli-type distribution. In the NILC schemes, we consider two types of compensation algorithms for dropped data: one of which is to replace the dropped data by that of the successfully captured at the concurrent...
This paper presents a finite-time observer for linear time-delay systems. In contrast to many observers, which normally estimate the system state in an asymptotic fashion, this observer estimates the exact system state in predetermined finite time. The finite-time observer proposed is achieved by updating the observer state based on actual and pass data of the observer. Simulation results are also...
Matrix series related to the solution of systems of linear algebraic equations are derived starting from the solution of a special type of a linear system of differential equations of the first order. The convergence of these series is adequate for computing efficiently approximate solutions of large systems of algebraic equations.
The convergence analysis of two-dimensional based integrated predictive iterative learning control (2D-IPILC) is presented for batch process in presence of output noises. In the 2D-IPILC method, iterative learning control (ILC) in the batch domain is integrated reasonably with real-time model predictive control (MPC) in the time domain. Based on the 2D system theory, system response of output tracking...
An Algebraic reconstruction technique (ART) with adaptive relaxation parameter based on hyperplane distance and data noise level is proposed in this paper. At each iteration of the proposed algorithm, the relaxation parameter for each hyperplane is adaptively adjusted based on the distance from the current vector to the hyperplane and the noise level in the measurement data. Numerical results show...
In this paper, we investigate some matrix preconditioning techniques for handling highly ill-conditioned matrices that often arise in Computational Electromagnetics (CEM). A preconditioning technique based on the use of Singular Value Decomposition (SVD) is proposed in this work to speed up the convergence of iterative methods when handling such matrices. Following this we review the Characteristic...
A simply constructed overlapped domain decomposition method based on the surface integral equation is presented. The buffer regions are limited to only a single layer of triangular mesh cells and the normal continuity of the currents across artificial boundaries is ensured by the Rao-Wilton-Glisson (RWG) basis functions defined over overlapped surfaces. Moreover, the overlapped currents belonging...
We propose a full order Linear Time-Varying (LTV) Luenberger observer for the rotor flux estimation of an induction motor. Introducing a suitable reduced-order Linear-Time-Invariant (LTI) system that is always observable and controllable, we show that any arbitrary LTI design and its quadratic Lyapunov certificates can be lifted to the higher-order original LTV dynamics obtaining the same certificates...
In this paper, a novel First-Order Sliding Mode (FOSM) Observer to estimate the state of a Linear Time-Invariant (LTI) system is presented. The main difference with other FOSM schemes is the selection of a time-varying surface, which is constructed using the dynamical structure of the system. The choice of this surface leads to finite-time convergence of the estimation error for any observable LTI...
The contribution of this paper is twofold. First, an upper estimate of the convergence (settling) time is calculated for the finite-time convergent control algorithm that drives the state of a series of integrators to the origin. To the best of our knowledge, such an estimate is obtained for the first time. Second, a novel fixed-time continuous control law is proposed for a chain of integrators of...
The research on sampled-data iterative learning control (SDILC) is briefly reviewed in this note. The concerned system models are listed as an classification of SDILC papers. Two problems of SDILC are presented aiming to at-sample tracking performance and intersample behavior. The literature is reviewed following the research group category. Some discussions on the further study are also given.
This paper tackles the problem of impulsive observer design for the class of linear time invariant system with sampled outputs. The proposed design approach includes continuous-time evolution and discrete jumps at specified time instants. The resulting observer is capable to track the system states in a predefined finite time. The estimation error is shown to be uniformly exponentially stable for...
This paper compares different Krylov methods based on short recurrences with respect to their efficiency whenimplemented on GPUs. The comparison includes BiCGSTAB, CGS, QMR, and IDR using different shadow space dimensions. These methods are known for their good convergencecharacteristics. For a large set of test matrices taken from theUniversity of Florida Matrix Collection, we evaluate the methods'performance...
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