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Bilinear Term

The Experts below are selected from a list of 1245 Experts worldwide ranked by ideXlab platform

Tingshu Hu – 1st expert on this subject based on the ideXlab platform

  • State-Space Approach to Modeling and Ripple Reduction in AC–DC Converters
    IEEE Transactions on Control Systems and Technology, 2013
    Co-Authors: Huong Pham, Hoeguk Jung, Tingshu Hu

    Abstract:

    This brief develops a systematic state-space approach to the modeling of boost type ac-dc converters and reduction of output ripples. The bridge rectifier voltage is modeled as a periodic disturbance whose harmonics have given frequencies but uncertain phases and magnitudes. These types of disturbances are described as the output of an external autonomous linear system, called an exogenous system, with uncertain initial conditions. The exogenous system is integrated with the boost converter as a whole system in state-space description. The whole system is a nonlinear system whose differential equation has a Bilinear Term, which is handled by an inclusion. Via a recently developed Lyapunov framework, the problem of ripple reduction is converted into a numerically efficient optimization problem, which involves linear matrix inequalities. The resulting feedback law is a simple linear state-feedback. Experimental results validate the effectiveness of the theoretical approach and design method.

  • ACC – Ripple reduction in AC-DC power converters via a Lyapunov approach
    2012 American Control Conference (ACC), 2012
    Co-Authors: Huong Pham, Hoeguk Jung, Tingshu Hu

    Abstract:

    This paper develops a systematic state-space approach to modeling of boost type AC-DC converters and reduction of the output ripples. The bridge rectifier voltage is modeled as a periodic disturbance whose harmonics have given frequencies but uncertain phases and magnitude. This type of disturbances are described as the output of an external autonomous linear system, called an exogenous system, with uncertain initial conditions. The exogenous system is integrated with the boost converter as a whole system in statespace description. The whole system is a nonlinear system whose differential equations has a Bilinear Term, which is handled by an inclusion. Via a recently developed Lyapunov framework, the problem of ripple reduction is converted into a numerically efficient optimization problem which involves linear matrix inequalities (LMIs). The resulting feedback law is a simple linear state-feedback. Experimental results validate the effectiveness of the theoretical approach and design method.

  • Stability and Robust Regulation of Battery-Driven Boost Converter With Simple Feedback
    IEEE Transactions on Power Electronics, 2011
    Co-Authors: Fidegnon Fassinou, Tingshu Hu

    Abstract:

    This paper investigates the problem of regulating the output voltage of a battery-driven boost converter, where the load is uncertain or changes within a certain range. The battery is modeled with a second order circuit with two capacitors. A state-space approach is developed for estimating the parameters of the battery. By using the state-space averaging method, the open-loop system for regulating the output voltage is described as a sixth order differential equation with a Bilinear Term and input constraints. A simple saturated state feedback is designed by solving some optimization problem with linear matrix inequality constraints. The optimized controller is very close to an integrator feedback. Using the newly developed Lyapunov method, we analyze the stability and regulation of the closed-loop Bilinear system including the battery dynamics. Computation shows that both the optimized state feedback and the integrator feedback can achieve practically global regulation in the presence of uncertain load and uncertain battery voltage. The results are validated by experimental systems. The effect of discontinuous conduction mode on transient response is discussed via simulation and experiment.

Silviu Ciochina – 2nd expert on this subject based on the ideXlab platform

  • A Proportionate Affine Projection Algorithm for the Identification of Sparse Bilinear Forms
    2019 International Symposium on Signals Circuits and Systems (ISSCS), 2019
    Co-Authors: Laura-maria Dogariu, Camelia Elisei-iliescu, Jacob Benesty, Constantin Paleologu, Silviu Ciochina

    Abstract:

    Identification of sparse impulse responses was addressed mainly in the last two decades with the development of the so-called “proportionate”-type algorithms. These algorithms are meant to exploit the sparseness of the systems that need to be identified, with the purpose of improving the convergence rate and tracking of the conventional adaptive algorithms used in this framework. Nevertheless, the system identification problem becomes more challenging when the parameter space is large. This issue can be addressed with tensor decompositions and modelling. In this paper, we aim to identify sparse Bilinear forms, in which the Bilinear Term is defined with respect to the impulse responses of a spatiotemporal model. In this context, we derive a proportionate affine projection algorithm for the identification of such Bilinear forms. Experimental results highlight the good behavior of the proposed solution.

  • Regularized Recursive Least-Squares Algorithms for the Identification of Bilinear Forms
    2018 International Symposium on Electronics and Telecommunications (ISETC), 2018
    Co-Authors: Camelia Elisei-iliescu, Constantin Paleologu, Silviu Ciochina, Cristian Stanciu, Cristian Anghel, Jacob Benesty

    Abstract:

    The system identification problem is more challenging when the parameter space becomes large. This paper addresses the identification of Bilinear systems based on the regularized recursive least-squares algorithm. Here, the Bilinear Term is defined with respect to the impulse responses of a spatiotemporal model. In order to improve the robustness of the algorithm in noisy environments, a variable-regularized version is also developed, where the regularization parameters are adjusted using an estimation of the signal-to-noise ratio. Simulation results outline the appealing features of these algorithms.

  • An Optimized LMS Algorithm for Bilinear Forms
    2018 International Symposium on Electronics and Telecommunications (ISETC), 2018
    Co-Authors: Laura-maria Dogariu, Jacob Benesty, Constantin Paleologu, Silviu Ciochina, Pablo Piantanida

    Abstract:

    In this paper we introduce an optimized version of the least-mean-square (LMS) algorithm, which is tailored for the particular case of Bilinear forms. In this context, the Bilinear Term is defined with respect to the impulse responses of a spatiotemporal model resembling a multiple-input/single-output system. Moreover, a comparison with the simplified version of the Kalman filter developed for Bilinear forms is provided. Simulation results show the good performance of the proposed algorithm.

Jacob Benesty – 3rd expert on this subject based on the ideXlab platform

  • A Proportionate Affine Projection Algorithm for the Identification of Sparse Bilinear Forms
    2019 International Symposium on Signals Circuits and Systems (ISSCS), 2019
    Co-Authors: Laura-maria Dogariu, Camelia Elisei-iliescu, Jacob Benesty, Constantin Paleologu, Silviu Ciochina

    Abstract:

    Identification of sparse impulse responses was addressed mainly in the last two decades with the development of the so-called “proportionate”-type algorithms. These algorithms are meant to exploit the sparseness of the systems that need to be identified, with the purpose of improving the convergence rate and tracking of the conventional adaptive algorithms used in this framework. Nevertheless, the system identification problem becomes more challenging when the parameter space is large. This issue can be addressed with tensor decompositions and modelling. In this paper, we aim to identify sparse Bilinear forms, in which the Bilinear Term is defined with respect to the impulse responses of a spatiotemporal model. In this context, we derive a proportionate affine projection algorithm for the identification of such Bilinear forms. Experimental results highlight the good behavior of the proposed solution.

  • Regularized Recursive Least-Squares Algorithms for the Identification of Bilinear Forms
    2018 International Symposium on Electronics and Telecommunications (ISETC), 2018
    Co-Authors: Camelia Elisei-iliescu, Constantin Paleologu, Silviu Ciochina, Cristian Stanciu, Cristian Anghel, Jacob Benesty

    Abstract:

    The system identification problem is more challenging when the parameter space becomes large. This paper addresses the identification of Bilinear systems based on the regularized recursive least-squares algorithm. Here, the Bilinear Term is defined with respect to the impulse responses of a spatiotemporal model. In order to improve the robustness of the algorithm in noisy environments, a variable-regularized version is also developed, where the regularization parameters are adjusted using an estimation of the signal-to-noise ratio. Simulation results outline the appealing features of these algorithms.

  • An Optimized LMS Algorithm for Bilinear Forms
    2018 International Symposium on Electronics and Telecommunications (ISETC), 2018
    Co-Authors: Laura-maria Dogariu, Jacob Benesty, Constantin Paleologu, Silviu Ciochina, Pablo Piantanida

    Abstract:

    In this paper we introduce an optimized version of the least-mean-square (LMS) algorithm, which is tailored for the particular case of Bilinear forms. In this context, the Bilinear Term is defined with respect to the impulse responses of a spatiotemporal model resembling a multiple-input/single-output system. Moreover, a comparison with the simplified version of the Kalman filter developed for Bilinear forms is provided. Simulation results show the good performance of the proposed algorithm.