YangQuan Chen

Prof. YangQuan Chen

University of California - Merced
orcid

Research Focus & Metrics

Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2018 in Communications in Nonlinear Science and Numerical Simulation
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Journal Article
Closed access
Sun  HongguangSun Hongguang
Sun Hongguang
YZYong Zhang
Yong Zhang
DBDumitru Baleanu
Dumitru Baleanu
WCWen Chen
Wen Chen
YangQuan ChenYangQuan Chen
YangQuan Chen

1 August 2009 in Automatica
Verified
Journal Article
Closed access
YLYan Li
Yan Li
YangQuan ChenYangQuan Chen
YangQuan Chen
IPIgor Podlubny
Igor Podlubny

1 March 2010 in Computers & Mathematics with Applications
Verified
Journal Article
Closed access
YLYan Li
Yan Li
YangQuan ChenYangQuan Chen
YangQuan Chen
IPIgor Podlubny
Igor Podlubny

1 November 2007 in IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)
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Journal Article
Closed access
HAHyo-Sung Ahn
Hyo-Sung Ahn
YangQuan ChenYangQuan Chen
YangQuan Chen
KMKevin L. Moore
Kevin L. Moore
In this paper, the iterative learning control (ILC) literature published between 1998 and 2004 is categorized and discussed, extending the earlier reviews presented by two of the authors. The papers includes a general introduction to ILC and a technical description of the methodology. The selected results are reviewed, and the ILC literature is categorized into subcategories within the broader division of application-focused and theory-focused results.

1 July 2008 in Control Engineering Practice
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Journal Article
Closed access
CMConcepción Monje
Concepción Monje
Blas M VinagreBlas M Vinagre
Blas M Vinagre
Vicente Feliu-BatlleVicente Feliu-Batlle
Vicente Feliu-Batlle
YangQuan ChenYangQuan Chen
YangQuan Chen

1 June 2009
Verified
Conference Paper
Closed access
YangQuan ChenYangQuan Chen
YangQuan Chen
Ivo PetrášIvo Petráš
Ivo Petráš
DXDingyu Xue
Dingyu Xue
Many real dynamic systems are better characterized using a non-integer order dynamic model based on fractional calculus or, differentiation or integration of non-integer order. Traditional calculus is based on integer order differentiation and integration. The concept of fractional calculus has tremendous potential to change the way we see, model, and control the nature around us. Denying fractional derivatives is like saying that zero, fractional, or irrational numbers do not exist. In this paper, we offer a tutorial on fractional calculus in controls. Basic definitions of fractional calculus, fractional order dynamic systems and controls are presented first. Then, fractional order PID controllers are introduced which may make fractional order controllers ubiquitous in industry. Additionally, several typical known fractional order controllers are introduced and commented. Numerical methods for simulating fractional order systems are given in detail so that a beginner can get started quickly. Discretization techniques for fractional order operators are introduced in some details too. Both digital and analog realization methods of fractional order operators are introduced. Finally, remarks on future research efforts in fractional order control are given.