Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

(528.78KB)
This is an Open Access publication published under CSC-OpenAccess Policy.
Identification and Control of Three-Links Electrically Driven Robot Arm Using Fuzzy Neural Networks
Salam A. Abdulkereem, Abduladhem A. Ali
Pages - 14 - 26     |    Revised - 31-03-2011     |    Published - 04-04-2011
Volume - 2   Issue - 1    |    Publication Date - March / April 2011  Table of Contents
MORE INFORMATION
KEYWORDS
Fuzzy Neural Control, Robot Control, Forward Adaptive Control, Inverse Control, Adaptive Systems
ABSTRACT
This paper uses a fuzzy neural network (FNN) structure for identifying and controlling nonlinear dynamic systems such three links robot arm. The equation of motion for three links robot arm derived using Lagrange’s equation. This equation then combined with the equations of motion for dc. servo motors which actuated the robot. For the control problem, we present the forward and inverse adaptive control approaches using the FNN. Computer simulation is performed to view the results for identification and control
CITED BY (1)  
1 Khurpade, J. B., Dhami, S. S., & Banwait, S. S. (2011, January). A Review of Fuzzy Logic Based Control of Robotic Manipulators. In ASME 2011 International Mechanical Engineering Congress and Exposition (pp. 241-257). American Society of Mechanical Engineers.
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 Rong-jong Wa and Po-Chen Chen,“Robust Neural-Fuzzy-Network Control for Robot Manipulator Including Actuator Dynamics”, IEEE Trans. Indst. Elect. vol. 53, no. 4, Aug. 2006.
2 S. J. Huang and J. S. Lee, “A stable self-organizing fuzzy controller for robotic motion control,” IEEE Trans. Ind. Electron., vol. 47, no. 2, pp. 421–428, Apr. 2000.
3 B. K. Yoo and W. C. Ham, “Adaptive control of robot manipulator using fuzzy compensator,” IEEE Trans. Fuzzy Syst., vol. 8, no. 2, pp. 186–199, Apr. 2000.
4 Y. C. Chang, “Neural network-based H-infinite tracking control for robotic systems,” Proc. Inst. Electr . Eng.—Control Theory Appl., vol. 147, no. 3, pp. 303–311, May 2000.
5 Y. H. Kim and F. L. Lewis, “Optimal design of CMAC neural-network controller for robot manipulators,” IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 30, no. 1, pp. 22–31, Feb. 2000.
6 K. S. Narendra and K. Parthasarathy, “Identification and control of dynamical system using neural networks,” IEEE Trans. Neural Networks, vol. 1, pp. 4–27, Jan. 1990.
7 K. Funahashi and Y. Nakamura, Approximation of dynamical systems by continuous-time recurrent neural network,” Neural Networks, vol.6, pp. 801–806, 1993.
8 L. Jin, P. N. Nikiforuk, and M. Gupta, “Approximation of discrete-time state-space trajectories using dynamic recurrent neural networks,” IEEE Trans. Automat. Contr., vol. 40, pp. 1266– 1270, July 1995.
9 C. C. Ku and K. Y. Lee, “Diagonal recurrent neural networks for dynamic systems control,” IEEE Trans. Neural Networks, vol. 6, pp.144–156, Jan. 1995.
10 Ching-Hung Lee and Ching-Cheng Teng, “Identification and Control of Dynamic Systems Using Recurrent Fuzzy Neural Networks”, IEEE Trans. Fuzzy system, vol. 8, no. 4, Aug. 2000
11 C. T. Lin and C. S. G. Lee, “Neural-network-based fuzzy logic control and decision system,” IEEE Trans. Computer. , vol. 40, pp. 1320–1336, Dec. 1991.
12 B. S. Chen, H. J. Uang, and C. S. Tseng, “Robust tracking enhancement of robot systems including motor dynamics: A fuzzy-based dynamic game approach,” IEEE Trans. Fuzzy Syst., vol. 6, no. 4, pp. 538–552,Nov. 1998.
13 C. Ishii, T. Shen, and K. Tamura, “Robust model following control for a robot manipulator,” Proc. Inst. Electr. Eng.—Control Theory Appl., vol. 144, no. 1, pp. 53–60, Jan. 1997
14 R. J. Schilling, Fundamentals of Robotics: Analysis and Control. Hoboken, NJ: Prentice-Hall, 1998.
15 Mark W.Spong, Seth H., M. Vidyasagar, “Robot Modeling and Control”, John Wiley and Sons, INC., 2001
16 Abdul Baqi, J.N., "Neuro-Fuzzy Control of robot Arm" MSC. Thesis, University of Basrah, College of Engineering, Feb. 2004.
17 Rong-Jong Wai, P. C. Chen, Chun-Yen Tu, “Robust Neural-fuzzy-network Control for Rigid-link Electrically Driven Robot Manipulator”, IEEE Trans. Ind. Electron., 30th annual conference, pp. 1328–1349, Nov. 2004.
18 Jorge Angels, ”Fundamentals of robotic mechanical systems: theory, methods and Algorithms”, Springer, 2003.
19 C. T. Leondes, "Fuzzy logic and expert systems applications", Academic Press, 1998.
20 Rong-Jong Wai, Chia-Chin Chu," Robust Petri Fuzzy-Neural-Network Control for Linear Induction Motor Drive", IEEE trans. on Ind. Elect. , Vol. 54, No. 1, pp. 177-189, Feb. 2007.
21 Rong-Jong Wai, Chia-Ming Liu," Design of Dynamic Petri Recurrent Fuzzy Neural Network and Its Application to Path-Tracking Control of Nonholonomic Mobile Robot", IEEE transactions on Ind. Elec., Vol. 56, NO. 7, pp.2667-2683, July 2009.
Mr. Salam A. Abdulkereem
University of Basrah - Iraq
salam_eng@yahoo.com
Dr. Abduladhem A. Ali
- Iraq