z-logo
open-access-imgOpen Access
Experimental Application of Predictive Controllers
Author(s) -
C. H. F. Silva,
Humberto Molinar Henrique,
Luís Cláudio Oliveira-Lopes
Publication year - 2012
Publication title -
journal of control science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.208
H-Index - 18
eISSN - 1687-5257
pISSN - 1687-5249
DOI - 10.1155/2012/159072
Subject(s) - model predictive control , control theory (sociology) , multivariable calculus , sequence (biology) , horizon , function (biology) , control (management) , computer science , control engineering , engineering , mathematical optimization , mathematics , artificial intelligence , chemistry , geometry , evolutionary biology , biology , biochemistry
Model predictive control (MPC) has been used successfully in industry. The basic characteristic of these algorithms is the formulation of an optimization problem in order to compute the sequence of control moves that minimize a performance function on the time horizon with the best information available at each instant, taking into account operation and plant model constraints. The classical algorithms Infinite Horizon Model Predictive Control (IHMPC) and Model Predictive Control with Reference System (RSMPC) were used for the experimental application in the multivariable control of the pilot plant (level and pH). The simulations and experimental results indicate the applicability and limitation of the control technique

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom