Predictive Control of Nonlinear Plant Using Piecewise-Linear Neural Model
D. Honc, P. Doležel, L. Gago
University of Pardubice
Abstract
A special form of a predictive controller is presented in this paper. Based on previous authors' work, a piecewise-linear neural model of nonlinear plant to be controlled is adopted to local linearization. The linearized model is then used for control action evaluation using a predictive controller. Although the linearization using piecewise-linear neural network is simple and efficient, it provides the model in a nonstandard form. Therefore, the proposed predictive controller is designed in order to handle that nonstandard model without any customization. At the end of the paper, the illustrative example demonstrates the main features of the introduced solution.
Full paper
Session
Linear and Non-linear Control System Design (Poster)
Reference
Honc, D.; Doležel, P.; Gago, L.: Predictive Control of Nonlinear Plant Using Piecewise-Linear Neural Model. Editors: Fikar, M. and Kvasnica, M., In Proceedings of the 2017 21st International Conference on Process Control (PC), Štrbské Pleso, Slovakia, June 6 – 9, 161–166, 2017.
BibTeX
@inProceedings{pc2017-019, | ||
author | = { | Honc, D. and Dole\v{z}el, P. and Gago, L.}, |
title | = { | Predictive Control of Nonlinear Plant Using Piecewise-Linear Neural Model}, |
booktitle | = { | Proceedings of the 2017 21st International Conference on Process Control (PC)}, |
year | = { | 2017}, |
pages | = { | 161-166}, |
editor | = { | Fikar, M. and Kvasnica, M.}, |
address | = { | \v{S}trbsk\'e Pleso, Slovakia}} |