PooGyeon Park
포항공과대학교 전기공학과 · 공학
PooGyeon Park 교수의 연구실은 주로 비선형 시스템의 안정성 분석, 신호 처리 알고리즘의 최적화, 그리고 상태 추정 기법에 초점을 맞추고 있습니다. 특히 시간 지연이 있는 시스템의 강인 안정성 기준, Lur'e 시스템의 절대 안정성 분석, 그리고 의사결정 기반 보정 알고리즘 설계 등에서 뛰어난 성과를 내고 있으며, 실시간 적용에 적합한 효율적이고 안정적인 알고리즘 개발을 추구합니다. 연구는 선형행렬부등식(LMI), 상태 추정 기반 알고리즘, 그리고 신호의 통계적 특성을 활용한 성능 분석을 중심으로 전개됩니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
This paper provides a new stability criterion for systems with time-invariant uncertain delays. Based on an improved upper bound for the inner product of two vectors, a new delay-dependent robust stability criterion is derived, which is shown by an example less conservative than existing stability criteria.
Presents stability criteria of sector- and slope-restricted Lur'e systems, in terms of linear matrix inequalities, by fully exploiting inherent properties of sector and slope restrictions in the time domain. Interpreting the time-domain criteria in the frequency domain, furthermore, supplies simpler expressions. Several examples show excellent performances of these criteria.
Presents some new square-root algorithms that allow more reliable computation of the state estimates, using, as far as possible, quantities obtained via orthogonal operations. New algorithms are given for covariance quantities and information quantities, and a new combined algorithm is also presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
This paper revisits a well-known Popov criterion for absolute stability analysis of multiple sector-restricted nonlinear time-invariant (NTI) Lur&apos;e systems. Extending the Brockett and Willems (1965) frequency-domain Popov criterion for a SISO system into a MIMO system with multiple sector-restrictions [0, <(Delta)over bar>], where <(Delta)over bar> is positive and diagonal, provides a claim that a system is absolutely stable if a function G(s) = <(Delta)over bar>(-1) +
This paper presents an improved mean-square deviation (MSD) analysis of the standard affine projection algorithm (APA) based on two distinctive features. First, the propagation model of the error covariance includes the cross-correlation between the current weight error vector and the prior measurement noises associated with the reused inputs; such a cross-correlation has merely been considered previously. Second, the analysis based on <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlin
