Hardware implementation of a neural network controller with an MCU and an FPGA for nonlinear systems

International Journal of Control, Automation and Systems

Volumn 4, Issue 5, 2006, Pages 567-574

  Kim, Sung Su ^a   Jung, Seul ^a  

^a Chungnam National University   (South Korea)

Author keywords

FPGA; MCU; Neural controller; Reference compensation technique; VHDL

Indexed keywords

MICRO-CONTROLLER UNIT (MCU); NEURAL CONTROLLERS; REFERENCE COMPENSATION TECHNIQUES; VERY HIGH SPEED INTEGRATED CIRCUIT HARDWARE DESCRIPTION LANGUAGE (VHDL);

COMPUTER HARDWARE DESCRIPTION LANGUAGES; FIELD PROGRAMMABLE GATE ARRAYS; LEARNING ALGORITHMS; MICROCONTROLLERS; NEURAL NETWORKS; NONLINEAR SYSTEMS; ONLINE SYSTEMS;

NONLINEAR CONTROL SYSTEMS;

EID: 33749455625     PISSN: 15986446     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. C. W. Anderson, "Learning to control an inverted pendulum using neural networks," IEEE Control Systems Magazine, vol. 9, no. 3, pp. 31-3 7, April 1989.
2. I. Fantoni and R. Lozano, "Global stabilization of the cart-pendulum system using saturation functions," Proc. of IEEE Conference on Decision and Control, pp. 4393-4398, 2003.
3. R. Yang, Y. Y. Kuen, and Z. Li, "Stabilization of a 2-DOF spherical pendulum on x-y table," Proc. of IEEE Conference on Control Applications, pp. 724-729, 2000.
4. R. J. Wai, J. D. Lee, and L. J. Chang, "Development of adaptive sliding mode control for nonlinear dual-axis inverted-pendulum system," Proc. of IEEE/ASME Conference on Advanced Intelligent Mechatronics, pp. 815-820, 2003.
5. T. Lahdhiri, C. Carnal, and A. Alouani, "Cart-pendulum balancing problem using fuzzy logic control," Proc. of Southeastern Conference, pp. 393-397, 1994.
6. M. E. Magana and F. Holzapfel, "Fuzzy-logic control of an inverted pendulum with vision feedback," IEEE Trans. on Education, vol. 41, no. 2, pp. 165-170, 1998.
7. T. H. Hung, M. F. Yeh, and H. C. Lu, "A pi-like fuzzy controller implementation for the inverted pendulum system," Proc. of IEEE Conference on Intelligent Processing Systems, pp. 218-222, 1997.
8. W. T. Miller, R. S. Sutton, and P. J. Werbos, Neural Networks for Control, The MIT Press, 1991.
9. S. Jung and T. C. Hsia, "Neural network inverse control techniques for PD controlled robot manipulator," Robotica, vol. 19, no. 3, pp. 305-314, 2000.
10. H. Miyamoto, K. Kawato, T. Setoyama, and R. Suzuki, "Feedback error learning neural network for trajectory control for of a robotic manipulator," Neural Networks, vol. 1, pp. 251-265, 1988
11. S. Jung and H. T. Cho, "Decentralized neural network reference compensation technique for PD controlled two degrees-of-freedom inverted pendulum," International Journal of Control, Automations, and System, vol. 2, no. 1, pp. 92-99, 2004.
12. S. Omatu, T. Fujinaka, and M. Yoshioka, "Neuro-pid control for inverted single and double pendulums," Proc. of IEEE Conf. on Systems, Man, and Cybernetics, pp. 8-11, 2000.
13. S.-S. Kim and S. Jung, "Hardware implementation of real time neural network controller with a DSP and an FPGA for nonlinear systems," Proc. of IEEE Conf. on Robotics and Automations, pp. 4639-4644, 2004.
14. M. Krips, T. Lammert, and A. Kummert, "FPGA implementation of a neural network for a real-time hand tracking system," Proc. of the First IEEE International Workshop on Electronic Design, Test and Applications, pp. 313-317, 2002.
15. M. Cristea, J. Khor, and M. McCormick, "FPGA fuzzy logic controller for variable speed generators," Proc. of the IEEE International Conference on Control Applications, pp. 301304, 2001.
16. A. Kongmunvattana and P. Chongstivatana, "A FPGA-based behavioural control system for a mobile robot," Proc. of the IEEE Asia-Pacific Conference on Circuits and Systems, pp. 759762, November 1998.
17. J. L. McClelland and D. E. Rumelhart, "Explorations in parallel distributed processing," The MIT Press, 1991.