:: ICCAS 2015 ::

WA07		Neural Networks and Fuzzy Systems
Time : 09:10~10:40 Room : 202		Chair : Naveen Kumar (National Institute of Technology Kurukshetra, India, )



09:10~09:25	WA07-1

Chaos in the fractional order Cellular Neural Network and its sychronization
Phuong Thanh Dam(Thai Nguyen University of Information and Communication Technology, Viet Nam), Cat Thuong Pham(VietNam Academy of Science and Technology, Viet Nam)

Chaos and its drive-response synchronization for a fractional-order cellular neural networks (CNN) are studied. It is found that chaos exists in the fractional-order system with six-cell. The phase sychronization of drive and response chaotic trajectories is investigated after that. These works based on lyapunov exponents (LE), lyapunov stability theory and numerical solving fractional-order system in Matlab enviroment.



09:25~09:40	WA07-2

Intelligent Control of Space Robot System using RBF Neural Network
Naveen Kumar(National Institute of Technology Kurukshetra, India, India), Vikas Panwar(Gautam Budhha University, Greater Noida, India, India)

Intelligent Control of Space Robot System using RBF Neural Network Naveen Kumar, Vikas Panwar (NIT, Kurukshetra, India) An intelligent controller is proposed for a space robot system with an attitude controlled base without joint acceleration measurements. The controller consists of computed torque type part, RBF neural network and an adaptive controller. The controller achieves the required tracking effectively. The controller is able to learn the existing structured and unstructured uncertainties in the system in online manner. The RBF network learns the unknown part of the space robot syst



09:40~09:55	WA07-3

Proposing a GPU Based Modified Fuzzy Nearest Neighbor Rule for Traffic Sign Detection
Peyman Hosseinzadeh, Junhyuk Hyun, Euntai Kim(Yonsei University, Korea, Republic of )

The purpose of this study is introducing a graphical process unit (GPU) implementation of a modified fuzzy nearest neighbor rule useful for traffic sign detection (TSD). The new method tries to detect road signs using color information in order to locate regions of interest. The candidate regions of interest are obtained by color information. Afterward, candidate regions are used for making histogram of oriented gradient (HOG) feature. Finally, the features are fed into the GPU-based modified fuzzy nearest neighbor in order to detect traffic signs. The proposed rule modifies the way for...



09:55~10:10	WA07-4

Head Gimbal Assembly Circuit with Vision Technique and Fuzzy C-Means Clustering
Rawinun Praserttaweelap, Somyot Kiatwanidvilai(King Mongkut’s Institute of Technology Ladkrabang, Thailand)

HGA circuits in 3 groups are good, bridging, and missing group. This research proposes use vision technique and Clustering. Blob analysis is the one of vision technique that it can measure the properties of image. The measurement properties from blob analysis are used in clustering technique. Fuzzy C-Means Clustering is the clustering technique which is grouped the measurement data into the cluster group based on the natural grouping of data. From the experiment results of this research, the clustering performance from Fuzzy C-Means Clustering is 99.11% accuracy based on 225 samples



10:10~10:25	WA07-5

Dissipative Filter Design for Takagi-Sugeno Fuzzy Neural Networks
Myo Taeg Lim, Kyu Chul Lee, Hyun Duk Choi, Dae Ki Kim, Choon Ki Ahn(Korea University, Korea, Republic of )

This paper proposes a novel dissipative filter for Takagi-Sugeno fuzzy Hopfield neural networks with time varying delay. This filter guarantees (Q, S,R)-α-dissipativity and is regarded as a generalization of some performance indices, such as H1 performance, passivity, and mixed H1/passivity. The linear matrix inequality (LMI) approach solving convex problem is used to obtain a gain matrix satisfying both (Q, S,R)-α-dissipativity and asymptotic stability of the error system. Some simulations are dealt with to validate the performance of the proposed method.



10:25~10:40	WA07-6

Fuzzy Logic Self-Tuning PID Control for a Single-Link Flexible Joint Robot Manipulator in the presence of Uncertainty
Ali Dehghani(Azad University Of khomeinishahr, Iran, Islamic Republic of), Hamed Khodadadi(Azad University Of Khomeinishahr, Iran, Islamic Republic of)

Fuzzy Logic Self-Tuning PID Control for a Single-Link Flexible Joint Robot Manipulator in the presence of Uncertainty Ali Dehghani, Hamed Khodadadi(Islamic Azad University of Khomeini shahr, Iran) Nowadays, flexible joint robots (FJR) manipulators are widely used at industry; however, these robots have several problems. These problems are in the joint and with links. Another problem is their complex dynamics that make control of this robot have some challenges. Non-linearity, interaction between loops and flexibility in the joint cause this problem. The present paper has focused to improve..