About Heating Plants Control System Developing on Basis of Neural Network Usage for PID-Regulator Parameters Optimization

Abstract:

An adaptive control system implementation is described. Such system is based on a neural network, used for online PID-regulator coefficients tuning. The backpropagation online training method is used. It is modified by adding a rule base. It contains conditions on choosing neural network learning rate. PID-regulator with neural tuner and conventional PID-regulator were used as regulators during the process of heating furnace control modeling. Such experiments were made for different loading furnace modes and setpoint schedules. The 11% economy of time on setpoint schedule realizing was achieved with the help of proposed neural tuner..

• Periodical: Applied Mechanics and Materials (Volume 682)
• Pages: 80-86
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.682.80
• Online since: October 2014
• Authors: Yuri Eremenko, Dmitry Poleshchenko, Anton Glushchenko
• Keywords: Adaptive Control Systems, Backpropagation Algorithm, Neural Network (NN), Neural Tuner, PID-Regulator

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