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Restricted structure predictive optimal control
Author(s) -
Grimble M. J.
Publication year - 2004
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.741
Subject(s) - setpoint , model predictive control , weighting , control theory (sociology) , pid controller , computer science , controller (irrigation) , optimal control , simple (philosophy) , control engineering , state space , quadratic equation , function (biology) , mathematical optimization , control (management) , engineering , mathematics , artificial intelligence , temperature control , medicine , agronomy , philosophy , statistics , geometry , epistemology , biology , radiology , evolutionary biology
The design of low‐order predictive optimal controllers, that involve a multi‐step cost index and future setpoint knowledge, is considered. The usual predictive controller is of high order and the aim is to develop simpler structures, suitable for applications where PID controllers might be employed. The system is assumed to be represented by a discrete‐time state‐space model, which is very general, and the quadratic cost‐function may include dynamic cost weighting terms. Using this approach, it is straightforward to generate a much lower‐order predictive controller and thereby simplify implementation. Even with a continuing improvement in computational power there are many good reasons why low‐order simple controllers have advantages in real applications. Copyright © 2004 John Wiley & Sons, Ltd.