A Novel Controller Dynamic Linearization-Based Model Free Adaptive Predictive Control for A Class Of Discrete Nonlinear Systems

DOI

10.2991/mecae-18.2018.80How to use a DOI?

Keywords

Model Free Adaptive Control; Data Driven Control; Model Free Adaptive Predictive Control; Controller Dynamic Linearization.

Abstract

In this work, a novel controller dynamic linearization based model free adaptive predictive control algorithm (CFDLc-MFAPC) for a class of discrete nonlinear system is proposed. This method introduces dynamic linearization parameters of ideal controller based on dynamic linearization technology, and combines predictive control idea to realize predictive function in controller. Compared with the model-based control method, the advantage of this method is mainly that it is a pure data driven control (DDC) method, and does not need any model information, but only needs the I/O data of the system. Moreover, the introduction of predictive control ideas not only improves the robustness of the system, but also realizes the model free adaptive prediction effect for the expected mutation. By this method, the robustness of the algorithm can be improved. The validity of the proposed method is verified by numerical simulations.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Danna Wang
PY  - 2018/03
DA  - 2018/03
TI  - A Novel Controller Dynamic Linearization-Based Model Free Adaptive Predictive Control for A Class Of Discrete Nonlinear Systems
BT  - Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-18.2018.80
DO  - 10.2991/mecae-18.2018.80
ID  - Wang2018/03
ER  -