Open AccessArtificial Neural Networks Models Based on ARX and State Space Forms and Adaptive Control PID/LQR of Systems Based on Peltier Cells
Author(s) -
Denis Fabricio Sousa de Sá,
João Viana da Fonseca Neto
Publication year - 2021
Language(s) - English
DOI - 10.31686/ijier.vol9.iss11.3540
Subject(s) - pid controller , control theory (sociology) , artificial neural network , adaptive control , linear quadratic regulator , control engineering , controller (irrigation) , computer science , digital control , parametric statistics , engineering , temperature control , artificial intelligence , mathematics , control (management) , electronic engineering , agronomy , biology , statistics
To improve the performance of a thermal plant based on Peltier cell actuators, an online parametric estimation via artificial neural networks and adaptive controller is presented. The control actions are based on adaptive digital controller and an adaptive quadratic linear regulator approaches. The Artificial neural networks topology is based on ARX and NARX models, and its training algorithms, such as accelerated backpropagation and recursive least square. The Control strategies are design-oriented to adaptive digital PID controller and quadratic linear regulator framework. The proposal is evaluated on temperature control of an object that is inside of a chamber.