Open access peer-reviewed chapter

A New Approach of the Online Tuning Gain Scheduling Nonlinear PID Controller Using Neural Network

By Ho Pham Huy Anh and Nguyen Thanh Nam

Submitted: June 23rd 2010Reviewed: October 27th 2010Published: April 19th 2011

DOI: 10.5772/15964

Downloaded: 2610

© 2011 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike-3.0 License, which permits use, distribution and reproduction for non-commercial purposes, provided the original is properly cited and derivative works building on this content are distributed under the same license.

How to cite and reference

Link to this chapter Copy to clipboard

Cite this chapter Copy to clipboard

Ho Pham Huy Anh and Nguyen Thanh Nam (April 19th 2011). A New Approach of the Online Tuning Gain Scheduling Nonlinear PID Controller Using Neural Network, PID Control Tamer Mansour, IntechOpen, DOI: 10.5772/15964. Available from:

Embed this chapter on your site Copy to clipboard

<iframe src="http://www.intechopen.com/embed/pid-control-implementation-and-tuning/a-new-approach-of-the-online-tuning-gain-scheduling-nonlinear-pid-controller-using-neural-network" />

Embed this code snippet in the HTML of your website to show this chapter

chapter statistics

2610total chapter downloads

2Crossref citations

More statistics for editors and authors

Login to your personal dashboard for more detailed statistics on your publications.

Access personal reporting

Related Content

This Book

Next chapter

Multivariable PID control of an Activated Sludge Wastewater Treatment Process

By Norhaliza Abdul Wahab, Reza Katebi and Jonas Balderud

Related Book

First chapter

Predictive PID Control of Non-Minimum Phase Systems

By Kenny Uren and George van Schoor

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities.

+3,550 Open Access Books

+57,400 Citations in Web of Science

+108,500 IntechOpen Authors and Academic Editors

+560,000 Unique visitors per month

More about us