The Experts below are selected from a list of 21873 Experts worldwide ranked by ideXlab platform
Nurettin Acir - One of the best experts on this subject based on the ideXlab platform.
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A generalized Lyapunov Stability Theory-based adaptive FIR filter algorithm with variable step sizes
Signal Image and Video Processing, 2017Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a novel approach to Lyapunov Stability Theory-based adaptive filter (LAF) design. The proposed design is based on the minimization of the Euclidean norm of the difference weight vector under negative definiteness constraint defined over a novel linear Lyapunov function. The proposed fixed step size LAF (FSS-LAF) algorithm is first obtained by using the method of Lagrangian multipliers. The FSS-LAF satisfying asymptotic Stability in the sense of Lyapunov provides a significant performance gain in the presence of a measurement noise. The Stability of the FSS-LAF algorithm is also statistically analyzed in this study. Moreover, gradient variable step size (VSS) algorithms are adapted to the FSS-LAF algorithm to further enhance the performance for the first time in this paper. These VSS algorithms are Benveniste (BVSS), Mathews and Farhang–Ang (FVSS) algorithms. Simulation results on system identification problems show that the bounds of step size for the FSS-LAF algorithm are verified, and especially, the BVSS-LAF and FVSS-LAF algorithms provide a better trade-off between steady-state mean square deviation error and convergence rate than other proposed algorithms.
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A novel adaptive filter design using Lyapunov Stability Theory
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2015Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a new approach to design an adaptive lter using Lyapunov Stability Theory. The design procedure is formulated as an inequality constrained optimization problem. Lagrange multiplier Theory is used as an optimization tool. Lyapunov Stability Theory is integrated into the constraint function to satisfy the asymptotic Stability of the proposed ltering system. The tracking capability is improved by using a new analytical adaptation gain rate, which has the ability to adaptively adjust itself depending on a sequential tracking square error rate. The fast and robust convergence ability of the proposed algorithm is comparatively examined by simulation examples.
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Lyapunov Stability Theory based complex valued adaptive filter design
Signal Processing and Communications Applications Conference, 2014Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:In this study, a novel complex valued adaptive filter algorithm is proposed satisfying Stability in the sense of Lyapunov. The prediction capability of the proposed algorithm is presented by using complex valued autoregressive process and wind signal in the literature. The proposed complex valued adaptive filter algorithm is compared with standard complex normalized least mean square algorithm and performed in a high performance.
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Lyapunov Stability Theory based adaptive filter algorithm for noisy measurements
International Conference on Computer Modelling and Simulation, 2013Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a Lyapunov Stability Theory based adaptive filter algorithm with a determined step size. The proposed algorithm thanks to its step size leads to a faster convergence rate and a lover misadjustment error in case of the noisy measurement environments. Also the proposed algorithm ensures to estimate the best optimal unknown weight vector by using a step size. Simulations on white and non-white Gaussian input signals justify the proposed algorithm for the noisy environments. The simulation results demonstrate good tracking capability and low misalignment error of the proposed algorithm in case of the noisy measurement environments for system identification problems.
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UKSim - Lyapunov Stability Theory Based Adaptive Filter Algorithm for Noisy Measurements
2013 UKSim 15th International Conference on Computer Modelling and Simulation, 2013Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a Lyapunov Stability Theory based adaptive filter algorithm with a determined step size. The proposed algorithm thanks to its step size leads to a faster convergence rate and a lover misadjustment error in case of the noisy measurement environments. Also the proposed algorithm ensures to estimate the best optimal unknown weight vector by using a step size. Simulations on white and non-white Gaussian input signals justify the proposed algorithm for the noisy environments. The simulation results demonstrate good tracking capability and low misalignment error of the proposed algorithm in case of the noisy measurement environments for system identification problems.
Yijia Cao - One of the best experts on this subject based on the ideXlab platform.
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A Lyapunov Stability Theory-Based Control Strategy for Three-Level Shunt Active Power Filter
Energies, 2017Co-Authors: Yijia CaoAbstract:The three-phase three-wire neutral-point-clamped shunt active power filter (NPC-SAPF), which most adopts classical closed-loop feedback control methods such as proportional-integral (PI), proportional-resonant (PR) and repetitive control, can only output 1st–25th harmonic currents with 10–20 kHz switching frequency. The reason for this is that the controller design must make a compromise between system Stability and harmonic current compensation ability under the condition of less than 20 kHz switching frequency. To broaden the bandwidth of the compensation current, a Lyapunov Stability Theory-based control strategy is presented in this paper for NPC-SAPF. The proposed control law is obtained by constructing the switching function on the basis of the mathematical model and the Lyapunov candidate function, which can avoid introducing closed-loop feedback control and keep the system globally asymptotically stable. By means of the proposed method, the NPC-SAPF has compensation ability for the 1st–50th harmonic currents, the total harmonic distortion (THD) and each harmonic content of grid currents satisfy the requirements of IEEE Standard 519-2014. In order to verify the superiority of the proposed control strategy, Stability conditions of the proposed strategy and the representative PR controllers are compared. The simulation results in MATLAB/Simulink (MathWorks, Natick, MA, USA) and the experimental results obtained on a 6.6 kVA NPC-SAPF laboratory prototype validate the proposed control strategy.
Engin Cemal Menguc - One of the best experts on this subject based on the ideXlab platform.
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A generalized Lyapunov Stability Theory-based adaptive FIR filter algorithm with variable step sizes
Signal Image and Video Processing, 2017Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a novel approach to Lyapunov Stability Theory-based adaptive filter (LAF) design. The proposed design is based on the minimization of the Euclidean norm of the difference weight vector under negative definiteness constraint defined over a novel linear Lyapunov function. The proposed fixed step size LAF (FSS-LAF) algorithm is first obtained by using the method of Lagrangian multipliers. The FSS-LAF satisfying asymptotic Stability in the sense of Lyapunov provides a significant performance gain in the presence of a measurement noise. The Stability of the FSS-LAF algorithm is also statistically analyzed in this study. Moreover, gradient variable step size (VSS) algorithms are adapted to the FSS-LAF algorithm to further enhance the performance for the first time in this paper. These VSS algorithms are Benveniste (BVSS), Mathews and Farhang–Ang (FVSS) algorithms. Simulation results on system identification problems show that the bounds of step size for the FSS-LAF algorithm are verified, and especially, the BVSS-LAF and FVSS-LAF algorithms provide a better trade-off between steady-state mean square deviation error and convergence rate than other proposed algorithms.
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A novel adaptive filter design using Lyapunov Stability Theory
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2015Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a new approach to design an adaptive lter using Lyapunov Stability Theory. The design procedure is formulated as an inequality constrained optimization problem. Lagrange multiplier Theory is used as an optimization tool. Lyapunov Stability Theory is integrated into the constraint function to satisfy the asymptotic Stability of the proposed ltering system. The tracking capability is improved by using a new analytical adaptation gain rate, which has the ability to adaptively adjust itself depending on a sequential tracking square error rate. The fast and robust convergence ability of the proposed algorithm is comparatively examined by simulation examples.
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Lyapunov Stability Theory based complex valued adaptive filter design
Signal Processing and Communications Applications Conference, 2014Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:In this study, a novel complex valued adaptive filter algorithm is proposed satisfying Stability in the sense of Lyapunov. The prediction capability of the proposed algorithm is presented by using complex valued autoregressive process and wind signal in the literature. The proposed complex valued adaptive filter algorithm is compared with standard complex normalized least mean square algorithm and performed in a high performance.
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Lyapunov Stability Theory based adaptive filter algorithm for noisy measurements
International Conference on Computer Modelling and Simulation, 2013Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a Lyapunov Stability Theory based adaptive filter algorithm with a determined step size. The proposed algorithm thanks to its step size leads to a faster convergence rate and a lover misadjustment error in case of the noisy measurement environments. Also the proposed algorithm ensures to estimate the best optimal unknown weight vector by using a step size. Simulations on white and non-white Gaussian input signals justify the proposed algorithm for the noisy environments. The simulation results demonstrate good tracking capability and low misalignment error of the proposed algorithm in case of the noisy measurement environments for system identification problems.
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UKSim - Lyapunov Stability Theory Based Adaptive Filter Algorithm for Noisy Measurements
2013 UKSim 15th International Conference on Computer Modelling and Simulation, 2013Co-Authors: Engin Cemal Menguc, Nurettin AcirAbstract:This paper presents a Lyapunov Stability Theory based adaptive filter algorithm with a determined step size. The proposed algorithm thanks to its step size leads to a faster convergence rate and a lover misadjustment error in case of the noisy measurement environments. Also the proposed algorithm ensures to estimate the best optimal unknown weight vector by using a step size. Simulations on white and non-white Gaussian input signals justify the proposed algorithm for the noisy environments. The simulation results demonstrate good tracking capability and low misalignment error of the proposed algorithm in case of the noisy measurement environments for system identification problems.
George Leitmann - One of the best experts on this subject based on the ideXlab platform.
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Screening policies for control of an infectious disease
Optimization Dynamics and Economic Analysis, 2000Co-Authors: George LeitmannAbstract:Utilizing Lyapunov Stability Theory constructively we deduce constant screening policies for use by a public health authority in the control of an infectious disease such as gonorrhea.
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A method for designing a stabilizing control for a class of uncertain linear delay systems
Dynamics and Control, 1994Co-Authors: Takashi Amemiya, George LeitmannAbstract:We present a simple method for designing stabilizing controllers for linear delay equations containing unmatched uncertainty. The methodology employed is based on differential inequalities rather than on Lyapunov Stability Theory.
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Lyapunov Stability Theory Based Control of Uncertain Dynamical Systems
Applied Mathematics in Aerospace Science and Engineering, 1994Co-Authors: George LeitmannAbstract:We present a controller design methodology for uncertain systems which is based on the constructive use of Lyapunov Stability Theory. The uncertainties, which are deterministic, are characterized by certain structural conditions and known as well as unknown bounds. As a consequence of the Lyapunov approach, the methodology is not restricted to linear or time-invariant systems. The robustness of these controllers in the presence of singular perturbations is considered. The situation in which the full state of the system is not available for measurement is also considered as are other generalizations. Applications of the proposed controller are noted.
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Deterministic control of uncertain systems via a constructive use of Lyapunov Stability Theory
System Modelling and Optimization, 1Co-Authors: George LeitmannAbstract:We present a controller design methodology for uncertain systems which is based on the constructive use of Lyapunov Stability Theory. The uncertainties, which are deterministic, are characterized by certain structural conditions and known as well as unknown bounds. As a consequence of the Lyapunov approach, the methodology is not restricted to linear or time-invariant systems. The robustness of these controllers in the presence of singular perturbations is considered. The situation in which the full state of the system is not available for measurement is also considered as are other generalizations. Applications of the proposed controller are noted.
Nurettin Acr - One of the best experts on this subject based on the ideXlab platform.
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An augmented complex-valued Lyapunov Stability Theory based adaptive filter algorithm
Signal Processing, 2017Co-Authors: Engin Cemal Meng, Nurettin AcrAbstract:A novel algorithm (ACLAF) is derived by using the LST and augmented statistics.The ACLAF algorithm provides a significant performance gain in noncircular signals.Rigorous analyses of the ACLAF algorithm are presented.Its performance is verified on both benchmark and real-world data. A novel augmented complex-valued Lyapunov Stability Theory (LST) based adaptive filter (ACLAF) algorithm is proposed for the widely linear adaptive filtering of noncircular complex-valued signals. After a candidate Lyapunov function is determined, the design procedure is formulated as an inequality constrained optimization problem by using augmented statistics and LST. Thus, the proposed algorithm has improved the adaptive filtering of noncircular complex-valued signals by a unified framework of the LST and augmented complex statistics. Moreover, we statistically show that the ACLAF algorithm converges to the optimal Wiener solution under stationary environments, the required condition of the step size for the Stability of the ACLAF algorithm is obtained by convergence in mean analysis and a new approach. In addition, the variance of the ACLAF algorithm is statically analysed in this study. The performance of the ACLAF algorithm is tested on circular and noncircular benchmark signals and on a real-world noncircular wind signal. Simulation results verify that the ACLAF algorithm outperforms complex-valued LST based adaptive filter (CLAF), complex-valued least mean square (CLMS), complex-valued normalized least mean square (CNLMS), augmented CLMS (ACLMS) and augmented CNLMS (ACNLMS) algorithms for adaptive prediction of noncircular signals in terms of prediction gain, convergence rate and mean square error (MSE). Also, the ACLAF algorithm enhances the prediction gain by more than 25% when compared to the other augmented algorithms.
