Inverse optimal control approach to model predictive control for linear system models

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

In this study, we propose an inverse optimal control based model predictive control approach. In inverse optimal control strategy, we firstly construct a stabilizing feedback control law and then search a meaningful cost functional. In that respect, we develop an alternative to solving the Riccati equation in MPC for linear time invariant system models. The control law is established with an appropriate scalar matrix which is found by using Big-Bang Big-Crunch(BB-BC) optimization algorithm. Simulations are done on a liquid level control system and the performance of the proposed method is compared with the performances of the classical model predictive, linear quadratic regulator and classical discrete time PID controller methods. The performance of the proposed controller is much better than the other controllers in respect to various criteria.

Original languageEnglish
Title of host publication2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages823-827
Number of pages5
ISBN (Electronic)9786050107371
Publication statusPublished - 2 Jul 2017
Event10th International Conference on Electrical and Electronics Engineering, ELECO 2017 - Bursa, Turkey
Duration: 29 Nov 20172 Dec 2017

Publication series

Name2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Volume2018-January

Conference

Conference10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Country/TerritoryTurkey
CityBursa
Period29/11/172/12/17

Bibliographical note

Publisher Copyright:
© 2017 EMO (Turkish Chamber of Electrical Enginners).

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