You can view the full text of this article for free using the link below.

Title: Lenient computation in controlling the nonlinear system based on adaptive error optimisation in microgrid

Authors: T. Yuvaraja; K. Ramya

Addresses: Department of EEE, Sri Sai Ram College of Engineering, Bangalore City, India ' Department of EEE, Sri Sai Ram College of Engineering, Bangalore City, India

Abstract: This manuscript describes the hybrid learning algorithm for training the error optimisation in an MIMO nonlinear system. The automated controller is designed using lenient computation technique with a Levenberg-Marquardt training algorithm. The designed controller is interfaced to a microgrid which has renewable energy sources like solar, wind, fuel cell, or smart battery as input and the output power generated by these sources can be utilised for various grid and atomised applications. The erudition capability and designing methodology of adaptive networks and sturdiness of PID controllers are described. Finally, the study illustrates an offline mode comparison of PID-based ANFIS and neural controllers in terms of settling time, steady state error and overshoot.

Keywords: lenient computation; proportional-integral-derivative; PID; ANFIS PID; ANN ARX model; neural network; renewable energy sources; microgrid.

DOI: 10.1504/IJIMR.2018.090941

International Journal of Intelligent Machines and Robotics, 2018 Vol.1 No.1, pp.5 - 15

Received: 26 Jan 2017
Accepted: 01 Feb 2017

Published online: 04 Apr 2018 *

Full-text access for editors Access for subscribers Free access Comment on this article