Journal of Professor & SPaC member

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Last Updated : 03/2016
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  • Dynamic output-feedback stabilisation for Markovian jump systems with incomplete transition description and input quantisation: linear matrix inequality approach

    Nam Kyu Kwon, Chan-eun Park, PooGyeon Park

    IET Control Theory & Applications

    Abstract In this study, a dynamic output-feedback stabilisation problem for Markovian jump systems (MJSs) with incomplete transition description and input quantisation is investigated. While the previous researches about output-feedback stabilisation for MJSs assumed that the transition rates are completely known, a more general situation where the transition rates are partly unknown is considered. Moreover, the proposed controller includes non-linear control part to eliminate the effect of input quantisation. Two numerical examples are provided to demonstrate the feasibility of the proposed dynamic output-feedback controller.
  • Steady-state mean-square deviation analysis of the sign subband adaptive filter

    J Shin, J Yoo, P Park

    Electronics Letters

    Abstract  The steady-state mean-square deviation (MSD) analysis of the sign subband adaptive filter is proposed. The proposed analysis is derived by the update recursion of the MSD using Price’s theorem and chi-distribution in stationary environments. Experimental results show that the proposed analysis is very close to simulated results not only for white input but also for coloured input signals.
  • Stabilization of a bias-compensated normalized least-mean-square algorithm for noisy inputs

    Sang Mok Jung, PooGyeon Park

    IEEE Transactions on Signal Processing

    Abstract  This paper proposes a stability-guaranteed bias-compensated normalized least-mean-square (BC-NLMS) algorithm for noisy inputs. The bias-compensated algorithms require the estimated input noise variance in the elimination process of the bias caused by noisy inputs. However, the conventional methods of estimating the input noise variance in those algorithms might cause the instability for a specific situation. This paper first analyzes the stability of the BC-NLMS algorithm by investigating the dynamics of both the mean deviation and the mean-square deviation in the BC-NLMS algorithm. Based on the analysis, the estimation of the input noise variance and the adjustment of the step size are carried out to perform a stabilization as well as a performance enhancement in terms of a steady-state error and a convergence rate. Simulations in system identification and acoustic echo cancellation scenarios with noisy inputs show that the proposed algorithm outperforms the existing bias-compensated algorithms in the aspect of the stability, the steady-state error, and the convergence rate.
  • Improved H∞ Control for Discrete-Time Markovian Jump Systems with Partly Unknown Transition Probabilities and Saturated Actuator

    In Seok Park, Nam Kyu Kwon, PooGyeon Park

    정보 및 제어 논문집

    Abstract This paper considers the problem of H∞ control for Markovian jump systems with partly unknown transition probabilities and input saturation. Using the convex property of normalized mode transition probabilities, less conservative H∞ stochastic stabilization conditions for discrete-time Markovian jump systems with partly unknown transition probabilities and input saturation are derived. Then, the derived conditions are represented as linear matrix inequalities (LMIs) conditions. The numerical examples will show that the proposed theorem exhibited better performance in view of the minimum cost
  • A variable step‐size diffusion affine projection algorithm

    JinWoo Yoo, IS Song, JaeWook Shin, PooGyeon Park

    International Journal of Communication Systems

    Abstract This paper presents a new variable step-size diffusion affine projection algorithm (VSS-DAPA) to advance the filter performance of the diffusion affine projection algorithm (DAPA). The proposed VSS strategy is developed for the DAPA, which can solve the distributed estimation problem over diffusion networks well. To obtain the optimal step size reasonably, we seek the update recursion of mean-square deviation (MSD) that is suitable for the DAPA. The step size is optimally given through the minimization for the MSD of the DAPA at each iteration. The derived step size through the MSD minimization improves the filter performance with respect to the convergence and the estimation error in steady state. The results based on simulations demonstrate that the proposed VSS-DAPA performs better than the existing algorithms with a system-identification scenario in diffusion network.
  • H∞ control for singular Markovian jump systems with incomplete knowledge of transition probabilities

    Nam Kyu Kwon, In Seok Park, PooGyeon Park

    Applied Mathematics and Computation

    AbstractThis paper proposes a H∞ state-feedback control for singular Markovian jump systems with incomplete knowledge of transition probabilities. Different from the previous results where the transition rates are completely known or the bounds of the unknown transition rates are given, a more general situation where the transition rates are partly unknown and the bounds of the unknown transition rates are also unknown is considered. Moreover, in contrast to the singular Markovian jump systems studied recently, the proposed method does not require any tuning parameters that arise when handling non-convex terms related to the mode-dependent Lyapunov matrices and the corresponding self-mode transition rates. Also, this paper uses all possible slack variables related to the transition rates into the relaxation process which contributes to reduce the conservatism. Finally, two numerical examples are provided to demonstrate the performance of H∞ mode-dependent control.
  • A combined reciprocal convexity approach for stability analysis of static neural networks with interval time-varying delays

    Won Il Lee, Seok Young Lee, PooGyeon Park

    Neurocomputing

    AbstractThis paper proposes a novel approach called a combined reciprocal convexity approach for the stability analysis of static neural networks with interval time-varying delays. The proposed approach deals with all convex-parameter-dependent terms in the time derivative of the Lyapunov-Krasovskii functional non-conservatively by extending the idea of the conventional reciprocal convexity approach. Based on the proposed technique and a new Lyapunov-Krasovskii functional, two improved delay-dependent stability criteria are derived in terms of linear matrix inequalities(LMIs). Some numerical examples are given to demonstrate the proposed results.
  • Polynomials‐based summation inequalities and their applications to discrete‐time systems with time‐varying delays

    Seok Young Lee, Won Il Lee, PooGyeon Park

    International Journal of Robust and Nonlinear Control

    AbstractThis paper proposes a novel summation inequality, say a polynomials-based summation inequality, which contains well-known summation inequalities as special cases. By specially choosing slack matrices, polynomial functions, and an arbitrary vector, it reduces to Moon’s inequality, a discrete-time counterpart of Wirtinger-based integral inequality, auxiliary function-based summation inequalities employing the same-order orthogonal polynomial functions. Thus, the proposed summation inequality is more general than other summation inequalities. Additionally, this paper derives the polynomials-based summation inequality employing first-order and second-order orthogonal polynomial functions, which contributes to obtaining improved stability criteria for discrete-time systems with time-varying delays.
  • Improved stability criteria for linear systems with interval time-varying delays: Generalized zero equalities approach

    Seok Young Lee, Won Il Lee, PooGyeon Park

    Applied Mathematics and Computation

    AbstractThis paper suggests first-order and second-order generalized zero equalities and constructs a new flexible Lyapunov–Krasovskii functional with more state terms. Also, by applying various zero equalities, improved stability criteria of linear systems with interval time-varying delays are developed. Using Wirtinger-based integral inequality, Jensen inequality and a lower bound lemma, the time derivative of the Lyapunov–Krasovskii functional is bounded by the combinations of various state terms including not only integral terms but also their interval-normalized versions, which contributes to make the stability criteria less conservative. Numerical examples show the improved performance of the criteria in terms of maximum delay bounds.
  • Polynomials-based integral inequality for stability analysis of linear systems with time-varying delays

    Seok Young Lee, Won Il Lee, PooGyeon Park

    Journal of the Franklin Institute

    Abstracthttps://scholar.google.co.kr/citations?view_op=view_citation&hl=ko&user=ktTQiqsAAAAJ&sortby=pubdate&citation_for_view=ktTQiqsAAAAJ:HtS1dXgVpQUC