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Model-based Predictive Control: A Practical Approach

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Model-based Predictive Control: A Practical Approach



08 May 2003 (Updated )

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FILES IN SUPPORT OF: Model-based predictive control: a practical approach, by J.A. Rossiter

Easily editable files to simulate three MIMO predictive control algorithms.

These files are intended as a support to this book to enable students to investigate predictive control algorithms from the formulation of the
prediction equations right through to the closed-loop simulation.

The code is mostly elementary MATLAB and is also transparent in structure. Hence the files form useful templates for algorithm modifications or to formulate the precise scenario or plots desired. Example files are provided to facilitate this. Some files allow for transfer function models and some for state space models and they cater for both SISO and MIMO processes and include systematic constraint handling. Most files do not use any MATLAB toolboxes but the few exceptions can easily be editted out with a small loss in functionality.

The files are provided free of charge and as such no guarantee is given as to their behaviour nor are they intended to be comprehensive. However, USERS are invited to contact the author if they discover either bugs or wish to suggest useful improvements.


This file inspired Mpc Tutorial Ii: Multivariable And State Space Mpc V2.0.

Required Products Control System Toolbox
Optimization Toolbox
MATLAB release MATLAB 6.0 (R12)
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Comments and Ratings (13)
02 Mar 2016 kamakshi

19 Jun 2015 mohamed meridjet

19 Jun 2015 mohamed meridjet

19 Jun 2015 mohamed meridjet

16 Aug 2010 Nicholas

19 Jul 2008 sudeendra kumar

18 May 2008 khansa bdirina

04 Dec 2007 Rahul Kanchan

This saves a lot of programming efforts.

16 Nov 2007 Fred Silva

26 Oct 2007 Farhad Bayat

21 Mar 2006 Ali Soltanzadeh

27 Nov 2004 narsimha rrao

thsi examples very very understading who was in basics and this prgromees very very usefuland helpful to my roject.

22 Apr 2004 Kai Hwang

Could be improved using the Neural networks approach

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