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Arbab Nighat Khizer
Beijing Institute of Technology, China

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Identification of Nonlinear System Based on Fuzzy Model with Enhanced Gradient Search Arbab Nighat Khizer; Dai Yaping; Amir Mahmood Soomro; Xu Xiang Yang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5261-5267

Abstract

Theidentification and modeling theory of nonlinear systems has always been challengingto researchers.  Fuzzy system due to its languagedescriptive way similar to human brain and deal with qualitative informationintelligently proves better choice for nonlinear system modeling over last fewdecades. The fuzzy system theory itself also has nonlinear characteristics thereforewhen establishing the fuzzy model of nonlinear system; it should be able towell describe the nonlinear characteristics. Takagi-Sugeno (TS) fuzzy systemsare not only suitable for modeling the nonlinear system due to combination ofthe good performance with the simple linear expressions, but also useful todesign the fuzzy controller. This paper proposed a new optimization algorithm namedas Enhanced Gradient Search (EGS) for identification of nonlinear system basedon TS fuzzy system. In proposed EGS, parameters of membership functions aretrained adaptively so as to calculate the gradient of cost function which isnecessary for minimizing the error. Using gradient information of costfunction, EGS applies in an innovative way such that it keeps and updates thebest search results at every training step during the optimization process. Theapplicability of EGS for TS fuzzy model shows splendid performance especially inmodeling of nonlinear system.
3DoF Model Helicopter with Hybrid Control Arbab Nighat Khizer; Dai Yaping; Syed Amjad Ali; Xu Xiang Yang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Dynamics of miniature unmanned helicopter are considered nonlinear and mutually coupled; therefore designing of a stable control becomes a big challenge for researchers. This paper addresses this issue by proposing a hybrid control methodology using both traditional and intelligent control. A 3DoF model helicopter system is used as a controlled platform. This hybrid control used PID as a traditional and fuzzy as an intelligent control so as to take the full advantage of advanced control theory. Proposed hybrid control is evaluated against the fuzzy and PID control through intensive simulation. Results verified that the proposed control has an excellent performance in static as well as dynamic environment as compared to individual PID and fuzzy control. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.5091
Co-Authors Amir Mahmood Soomro Dai Yaping Syed Amjad Ali Xu Xiang Yang Xu Xiang Yang