Implementation of New Predictive Control Based Volterra Model for Fast Dynamic Systems Using Microcontrollers: Real Time Application

被引:0
|
作者
Hmidene A. [1 ]
Bennasr H. [2 ]
M'Sahli F. [3 ]
机构
[1] Department of Electrical engineering, Higher Institute of Technological Studies Erriadh City, P. O. B. 35, Sousse
[2] Department of Electrical engineering, Higher Institute of Technological Studies EL Bustan City, P. O. B 88A, Sfax
[3] Department of Electrical Engineering, National Engineering School of Tunis, P. O. B. 176, Tunis
来源
Periodica polytechnica Electrical engineering and computer science | 2024年 / 68卷 / 02期
关键词
fast systems; neural network; predictive control; STM32; volterra model;
D O I
10.3311/PPee.23033
中图分类号
学科分类号
摘要
This paper presents a new contribution in the implementation of Volterra model predictive control for fast dynamics systems. The control approaches considered results on a switch paradigm that combine an online part based on suboptimal solution and an offline part referred to an offline neural network controller. The proposed approach has an advantage in comparison with nonlinear optimization-based control schemes. A real time application on STM32 to control a boost converter is studied and the results show very remarkable performances in time computing. © 2024 Budapest University of Technology and Economics. All rights reserved.
引用
收藏
页码:115 / 123
页数:8
相关论文
共 50 条
  • [1] Fast constrained nonlinear model predictive control for implementation on microcontrollers
    Ndje, Martial
    Bitjoka, Laurent
    Boum, Alexandre Teplaira
    Mbogne, David Jaures Fotsa
    Busoniu, Lucian
    Kamgang, Jean Claude
    Djogdom, Gilde Vanel Tchane
    IFAC PAPERSONLINE, 2021, 54 (04): : 19 - 24
  • [2] Real-Time Implementation of Model Predictive Control for Flow Control Application
    Rosli, Nurfatihah Syalwiah
    Ibrahim, Rosdiazli
    2014 5TH INTERNATIONAL CONFERENCE ON INTELLIGENT AND ADVANCED SYSTEMS (ICIAS 2014), 2014,
  • [3] Real-time Implementation of Nonlinear Model Predictive Control for Mechatronic Systems Using a Hybrid Model
    Loew, Stefan
    Obradovic, Dragan
    2018 IEEE 14TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2018, : 164 - 167
  • [4] Real-time implementation of model predictive control
    Bleris, LG
    Kothare, MV
    ACC: PROCEEDINGS OF THE 2005 AMERICAN CONTROL CONFERENCE, VOLS 1-7, 2005, : 4166 - 4171
  • [5] Implementation of model predictive control using real-time multiprocessing computing
    Hassapis, G
    MICROPROCESSORS AND MICROSYSTEMS, 2003, 27 (07) : 327 - 340
  • [6] Real-time Nonlinear Model Predictive Control Predictive control for mechatronic systems using a hybrid model
    Loew, Stefan
    Obradovic, Dragan
    ATP MAGAZINE, 2018, (08): : 46 - 52
  • [7] Implementation of a fast dynamic clamp using real time linux
    Butera, RJ
    Wilson, CG
    Rinzel, J
    Smith, JC
    FASEB JOURNAL, 1999, 13 (04): : A424 - A424
  • [8] A Fast Nonlinear Model Predictive Control Strategy for Real-time Motion Control of Mechanical Systems
    Chen, Yutao
    Cuccato, Davide
    Bruschetta, Mattia
    Beghi, Alessandro
    2017 IEEE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM), 2017, : 1780 - 1785
  • [9] An Efficient Linearized Volterra Series for Nonlinear Model Predictive Control in Dynamic Systems
    Zeynal, Hossein
    Zakaria, Zuhaina
    Kor, Ahmad
    Yaghoobi, Ahmad
    2020 IEEE INTERNATIONAL CONFERENCE ON POWER AND ENERGY (PECON 2020), 2020, : 415 - 419
  • [10] Recursive Model Predictive Control for Fast Varying Dynamic Systems
    Lu, Da
    Zhao, Guangzhou
    Qi, Donglian
    INTELLIGENT COMPUTING FOR SUSTAINABLE ENERGY AND ENVIRONMENT, 2013, 355 : 104 - 112