International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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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)
  • Published : 2006.10.01
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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

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