A Suboptimal Approach to Real-time Model Predictive Control of Nonlinear Systems

被引：10
|
作者：
Graichen, Knut [1 ]
Egretzberger, Markus [2 ]
Kugi, Andreas [2 ]
机构：
[1] Univ Ulm, Inst Mess Regel & Mikrotech, D-89081 Ulm, Germany
[2] TU Wien, Inst Automatisierungs & Regelungstech, A-1040 Vienna, Austria
来源：
AT-AUTOMATISIERUNGSTECHNIK | 2010年 / 58卷 / 08期
关键词：
Model Predictive Control; nonlinear systems; real-time feasibility; time and memory efficient computation; suboptimality; incremental improvement; RECEDING-HORIZON CONTROL; STABILITY; OPTIMALITY; SCHEME;
D O I：
10.1524/auto.2010.0860
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper describes a fast Model Predictive Control (MPC) scheme for nonlinear systems subject to control constraints. The MPC scheme computes a suboptimal solution of the underlying optimal control problem that is incrementally refined over the runtime of the process. The MPC scheme uses a fixed number of iterations in each sampling step and allows for a time and memory efficient computation of the single iterations. The control performance, the real-time feasibility as well as the incremental improvement of the MPC scheme are demonstrated for a laboratory overhead crane with a sampling time of 2 ms.
引用
收藏
页码：447 / 456
页数：10
相关论文
共 50 条
  • [1] Real-Time Economic Model Predictive Control of Nonlinear Process Systems
    Ellis, Matthew
    Christofides, Panagiotis D.
    AICHE JOURNAL, 2015, 61 (02) : 555 - 571
  • [2] 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
  • [3] Real-time distributed control: A fuzzy and model predictive control approach for a nonlinear problem
    Benitez-Perez, H.
    NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2008, 2 (02) : 474 - 490
  • [4] A real-time framework for model predictive control of continuous-time nonlinear systems
    DeHaan, Darryl
    Guay, Martin
    2005 44TH IEEE CONFERENCE ON DECISION AND CONTROL & EUROPEAN CONTROL CONFERENCE, VOLS 1-8, 2005, : 957 - 962
  • [5] A real-time framework for model-predictive control of continuous-time nonlinear systems
    DeHaan, Darryl
    Guay, Martin
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2007, 52 (11) : 2047 - 2057
  • [6] 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
  • [7] 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
  • [8] A new real-time method for Nonlinear model predictive control
    DeHaan, Darryl
    Guay, Martin
    ASSESSMENT AND FUTURE DIRECTIONS OF NONLINEAR MODEL PREDICTIVE CONTROL, 2007, 358 : 537 - +
  • [9] Real-Time Nonlinear Model Predictive Control of a Virtual Motorcycle
    Bruschetta, Mattia
    Picotti, Enrico
    De Simoi, Andrea
    Chen, Yutao
    Beghi, Alessandro
    Nishimura, Masatsugu
    Tezuka, Yoshitaka
    Ambrogi, Francesco
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2021, 29 (05) : 2214 - 2222
  • [10] Real-Time Nonlinear Model Predictive Control for Microgrid Operation
    Nurkanovic, Armin
    Mesanovic, Amer
    Zanelli, Andrea
    Frison, Gianluca
    Frey, Jonathan
    Albrecht, Sebastian
    Diehl, Moritz
    2020 AMERICAN CONTROL CONFERENCE (ACC), 2020, : 4989 - 4995
12345