Cheung-Chieh Ku

Prof. Cheung-Chieh Ku

orcid

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

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

Representative Publications

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1 August 2010 in Fuzzy Sets and Systems
Verified
Journal Article
Closed access
WCWen-Jer Chang
Wen-Jer Chang
Cheung-Chieh KuCheung-Chieh Ku
Cheung-Chieh Ku
PHPei-Hwa Huang
Pei-Hwa Huang

1 June 2010 in Journal of the Franklin Institute
Verified
Journal Article
Closed access
Cheung-Chieh KuCheung-Chieh Ku
Cheung-Chieh Ku
PHPei-Hwa Huang
Pei-Hwa Huang
Wen-Jer ChangWen-Jer Chang
Wen-Jer Chang

27 May 2024 in IEEE Transactions on Fuzzy Systems
Verified
Journal Article
Open access
Wen-Jer ChangWen-Jer Chang
Wen-Jer Chang
YLYann-Horng Lin
Yann-Horng Lin
YLYi-Chen Lee
Yi-Chen Lee
Cheung-Chieh KuCheung-Chieh Ku
Cheung-Chieh Ku
A Fuzzy Sliding Mode (FSM) tracking approach is proposed via Interval Type-2 (IT-2) Takagi-Sugeno Fuzzy Model (T-SFM) to complete Formation and Containment (F-and-C) tasks for Nonlinear Multi-Agent Systems (NMASs) with uncertainties and disturbances. Using Imperfect Premise Matching (IPM) approach, the IT-2 F-and-C Fuzzy Controllers (FCs) are designed in accordance with the IT-2 T-SFM. Different from the existing research, the individual tracking FC for each leader is proposed to complete the formation tasks and assignment of whole system dynamics. The stability analysis process is also simplified for ensuring the formation purpose. Benefiting from the advantage, the FSM control is conveniently combined into the FC design to upgrade the performance of leaders. For followers, the analysis methods of linear Multi-Agent (M-A) systems are extended to solve the containment analysis problem without the additional assumption by virtue of the IT-2 T-SFM representation. To deal with the disturbance effect, the passive constraints are combined into the analysis process. Finally, the proposed F-and-C FCs design method is applied to a Nonlinear Multi-Ships System (NMSS) to illustrate the advantage.


1 July 2009 in ISA Transactions
Verified
Journal Article
Closed access
Wen-Jer ChangWen-Jer Chang
Wen-Jer Chang
Cheung-Chieh KuCheung-Chieh Ku
Cheung-Chieh Ku
PHPei-Hwa Huang
Pei-Hwa Huang
WCWei Chang
Wei Chang

19 May 2008 in International Journal of Systems Science
Verified
Journal Article
Closed access
Wen-Jer ChangWen-Jer Chang
Wen-Jer Chang
Cheung-Chieh KuCheung-Chieh Ku
Cheung-Chieh Ku
WCWei Chang
Wei Chang
The article considers the analysis and synthesis problem for the discrete nonlinear systems, which are represented by the discrete affine Takagi–Sugeno (T–S) fuzzy models. The state feedback fuzzy controller design methodology is developed to guarantee that the affine T–S fuzzy models achieve Lyapunov stability and strict input passivity. In order to find a suitable fuzzy controller, an Iterative Linear Matrix Inequality (ILMI) algorithm is employed in this article to solve the stability conditions for the closed-loop affine T–S fuzzy models. Finally, the application of the proposed fuzzy controller design methodology is manifested via a numerical example with computer simulations.