Neural Network on FPGA for PID Controller

Evolution of bio-inspired concepts like neural networks learning have attracted the attention of complex and intelligent systems because of a growing interest in automatic design, capable of adaptation and fault tolerance. Artificial neural network have found widespread deployment in different areas of classification, perception, control application etc. Control Objects are becoming more complex, especially for the unknown parameters or slow changes in large delay, time-varying, nonlinear complex systems, with delay or random interference. PID controller is well known industrial used controller. Combining the artificial neural networks, genetic algorithms or other intelligent control theories with conventional PID control, can overcome the disadvantages of conventional PID control. This paper presents the hardware implementation of neural network using FPGAs. Digital system architecture is presented using Very High Speed Integrated Circuits Hardware Description Language (VHDL) and is implemented in FPGA.