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Hardware Implementation of a Neural Network Controller with an MCU and an FPGA for Nonlinear Systems  

Kim Sung-Su (BK21 Mechatronics Group, Chungnam National University)
Jung Seul (BK21 Mechatronics Group, Chungnam National University)
Publication Information
International Journal of Control, Automation, and Systems / v.4, no.5, 2006 , pp. 567-574 More about this Journal
Abstract
This paper presents the hardware implementation of a neural network controller for a nonlinear system with a micro-controller unit (MCU) and a field programmable gate array (FPGA) chip. As an on-line learning algorithm of a neural network, the reference compensation technique has been implemented on an MCU, while PID controllers with other functions such as counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The developed neural control hardware has been tested for balancing the inverted pendulum while controlling a desired trajectory of a cart as a nonlinear system.
Keywords
FPGA; MCU; neural controller; reference compensation technique; VHDL;
Citations & Related Records

Times Cited By Web Of Science : 1  (Related Records In Web of Science)
Times Cited By SCOPUS : 4
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