Seok Young Lee, Won Il Lee, PooGyeon Park
International Journal of Robust and Nonlinear Control
AbstractThis paper suggests a generalized zero equality lemma for summations, which leads to making a new Lyapunov–Krasovskii functional with more state terms in the summands and thus applying various zero equalities for deriving stability criteria of discrete-time systems with interval time-varying delays. Also, using a discrete-time counter part of Wirtinger-based integral inequality, Jensen inequality, and a lower bound lemma for reciprocal convexity, the forward difference of the Lyapunov–Krasovskii functional is bounded by the combinations of various state terms including not only summation terms but also their interval-normalized versions, which contributes to making the criteria less conservative. Numerical examples show the improved performance of the criteria in terms of maximum delay bounds.
JinWoo Yoo, JaeWook Shin, Insun Song, P Park
International Journal of Communication Systems
AbstractThis paper proposes a novel robust affine projection sign algorithm (R-APSA) through a modified criterion that consists of the Euclidean norm of the sum of the difference between the present weight vector and the previous weight vectors. Because the filter update equation of the proposed R-APSA is obtained from the modified criterion, it has robustness against the high power of measurement noises. Moreover, due to the characteristic inherent in the original APSA, the proposed R-APSA performs well even though impulsive noises occur. Simulation results verify that the proposed R-APSA attains smaller steady-state errors than the existing released algorithms.
Sang Mok Jung, Ji-Hye Seo, PooGyeon Park
Circuits, Systems, and Signal Processing
A novel diffusion normalized least-mean-square algorithm is proposed for distributed network. For the adaptation step, the upper bound of the mean-square deviation (MSD) is derived instead of the exact MSD value, and then, the variable step size is obtained by minimizing it to achieve fast convergence rate and small steady-state error. For the diffusion step, the individual estimate at each node is constructed via the weighted sum of the intermediate estimates at its neighbor nodes, where the weights are designed by using a proposed combination method based on the MSD at each node. The proposed MSD-based combination method provides effective weights by using the MSD at each node as a reliability indicator. Simulations in a system identification context show that the proposed algorithm outperforms other algorithms in the literatures.
Ju-man Song, PooGyeon Park
Abstract This paper introduces an optimal variable step-size affine projection algorithm for the modified filtered-x active noise control systems. First, the recursion form of the error covariance from the tap weight update equation is constructed, not ignoring the dependency between the estimation error and the secondary noise signal. Such consideration has not been concerned previously for the analysis of the modified filtered-x affine projection algorithm. Second, a recursion form of the mean square deviation is derived from that of the error covariance. From the recursion form, an optimal step size is decided to get the fastest convergence rate. Both the recursion forms of the mean square deviation and the optimal step size require scalar additions and multiplications that do not contribute to the overall complexity seriously. The simulation results on the active noise control environments show both fast convergence rate and low steady-state error.
Nam Kyu Kwon, Bum Yong Park, PooGyeon Park
Optimal Control Applications and Methods
Abstract This paper proposes less conservative stabilization conditions for Markovian jump systems with incompleteknowledge of transition probabilities and input saturation. The transition rates associated with the transitionprobabilities are expressed in terms of three properties, which do not require the lower and upper bounds ofthe transition rates, differently from other approaches in the literature. The resulting conditions are convertedinto the second-order matrix polynomial of the unknown transition rates. The polynomial can be representedas quadratic form of vectorized identity matrices scaled by one and the unknown transition rates. And then,the LMI conditions are obtained from the quadratic form. Also, an optimization problem is formulated to?nd the largest estimate of the domain of attraction in mean square sense of the closed-loop systems. Finally,two numerical examples are provided to illustrate the effectiveness of the derived stabilization conditions.Copyright ⓒ 2016 John Wiley & Sons, Ltd.
Ji-Hye Seo, Sang Mok Jung, PooGyeon Park
Digital Signal Processing
Abstract This paper proposes a novel diffusion subband adaptive filtering algorithm for distributed networks. To achieve a fast convergence rate and small steady-state errors, a variable step size and a new combination method is developed. For the adaptation step, the upper bound of the mean-square deviation (MSD) of the algorithm is derived and the step size is adaptive by minimizing it in order to attain the fastest convergence rate on every iteration. Furthermore, for a combination step realized by a convex combination of the neighbor-node estimates, the proposed algorithm uses the MSD, which contains information on the reliability of the estimates, to determine combination coefficients. Simulation results show that the proposed algorithm outperforms the existing algorithms in terms of the convergence rate and the steady-state errors.
KD Badgujar, PG Park
Abstract The core power distribution in the advanced high temperature prismatic reactor (AHTPR 625) belonging to the high temperature gas cooled reactor family is controlled using the constrained receding-horizon control algorithm. The outputs from each region of the reactor core are used as the inputs of the system. The reactor model is based on the two-point-coupled xenon oscillation model. It utilises the nonlinear xenon and iodine balance equations along with the one-group, one-dimensional neutron diffusion equation including feedback with a power coefficient. Axially, the reactor core is divided into two regions. Each region has one input and one output. These regions are coupled with each other. The proposed control method demonstrates very fast response to input flux change in the form of a step and ramp change without any residual flux oscillations between the regions of the reactor core. The constrained receding-horizon control problem involves solving an optimisation problem for finite future samples and obtaining the control with few samples. Among the few constrained control samples only the first one is applied and the process to solve the optimisation problem is repeated again.
PooGyeon Park, Nam Kyu Kwon, Bum Yong Park
Journal of the Franklin Institute
Abstract This paper proposes a state-feedback controller design for linear parameter-varying systems with interval uncertain parameters that are interval-type uncertain weight functions for convex combinations of linear subsystems. The proposed controller hires secondary convex parameters generated through the lower and upper boundaries of the interval uncertain parameters. The resulting stabilization condition is expressed in terms of parameterized linear matrix inequalities, which are then converted into linear matrix inequalities using a parameter relaxation technique. The simulation results illustrate the robustness of the proposed controller.
Sang Mok Jung, Ji-Hye Seo, PooGyeon Park
Signal Processing, IET
Abstract This paper proposes a fast and precise adaptive filtering algorithm for online estimation under a non-negativity constraint. A novel variable step-size (VSS) non-negative normalised least-mean-square (NLMS)-type algorithm based on the mean-square deviation (MSD) analysis with a non-negativity constraint is derived. The NLMS-type algorithm under the non-negativity constraint is derived by using the gradient descent of the given cost function and the fixed-point iteration method. Furthermore, the VSS derived by minimising the MSD yields improvement of the filter performance in the aspects of the convergence rate and the steady-state estimation error. Simulation results show that the proposed algorithm outperforms existing algorithms.