Hardware Implementation of a Neuralnetwork Controler with an MCU and an FPGA for a Nonlinear System
| Authors: | Jung Seul, Chungnam National Univ., Korea, Republic of
Kim S., Chungnam National Univ., Korea, Republic of |
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| Topic: | 3.2 Cognition and Control ( AI, Fuzzy, Neuro, Evolut.Comp.) |
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| Session: | Neural Networks in Modelling and Control |
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| Keywords: | Reference compensation technique, FPGA, VHDL, ARM, neural controller |
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Abstract
This paper presents the hardware implementation of a neural network controller for a nonlinear system. As a learning algorithm for a neural network, the reference compensation technique has been implemented on a low cost micro-controller unit (MCU), while PID controllers with 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 neural controller has been tested for controlling the inverted pendulum as a nonlinear system.
