LQR based optimal control of chaotic dynamical systems

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

This article studies the linear quadratic regulator (LQR)-based optimal control law for chaotic dynamical system. First,we show a systematic and effective framework for modelling of chaotic system by considering the dynamics of bouncing ball on sinusoidally oscillating surface and explore the similarity between dynamics of the standard chaoticmap and bouncing ball dynamics. Then we investigated the discrete LQR optimal control technique to the control of chaotic system. The investigated design method is conceptually simple and computationally efficient. The effectiveness of the design method is demonstrated by simulation results.

Original languageEnglish
Pages (from-to)104-112
Number of pages9
JournalInternational Journal of Modelling and Simulation
Volume35
Issue number3-4
DOIs
Publication statusPublished - 2015

Fingerprint

Chaotic Dynamical Systems
Regulator
Dynamical systems
Optimal Control
Chaotic systems
Chaotic System
Design Method
Ball
Modeling
Simulation

All Science Journal Classification (ASJC) codes

  • Software
  • Modelling and Simulation
  • Mechanics of Materials
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

@article{bb6ef2a493bb47f685b20ecde1d26a95,
title = "LQR based optimal control of chaotic dynamical systems",
abstract = "This article studies the linear quadratic regulator (LQR)-based optimal control law for chaotic dynamical system. First,we show a systematic and effective framework for modelling of chaotic system by considering the dynamics of bouncing ball on sinusoidally oscillating surface and explore the similarity between dynamics of the standard chaoticmap and bouncing ball dynamics. Then we investigated the discrete LQR optimal control technique to the control of chaotic system. The investigated design method is conceptually simple and computationally efficient. The effectiveness of the design method is demonstrated by simulation results.",
author = "Choudhary, {Santosh Kumar}",
year = "2015",
doi = "10.1080/02286203.2016.1142275",
language = "English",
volume = "35",
pages = "104--112",
journal = "International Journal of Modelling and Simulation",
issn = "0228-6203",
publisher = "ACTA Press",
number = "3-4",

}

LQR based optimal control of chaotic dynamical systems. / Choudhary, Santosh Kumar.

In: International Journal of Modelling and Simulation, Vol. 35, No. 3-4, 2015, p. 104-112.

Research output: Contribution to journalArticle

TY - JOUR

T1 - LQR based optimal control of chaotic dynamical systems

AU - Choudhary, Santosh Kumar

PY - 2015

Y1 - 2015

N2 - This article studies the linear quadratic regulator (LQR)-based optimal control law for chaotic dynamical system. First,we show a systematic and effective framework for modelling of chaotic system by considering the dynamics of bouncing ball on sinusoidally oscillating surface and explore the similarity between dynamics of the standard chaoticmap and bouncing ball dynamics. Then we investigated the discrete LQR optimal control technique to the control of chaotic system. The investigated design method is conceptually simple and computationally efficient. The effectiveness of the design method is demonstrated by simulation results.

AB - This article studies the linear quadratic regulator (LQR)-based optimal control law for chaotic dynamical system. First,we show a systematic and effective framework for modelling of chaotic system by considering the dynamics of bouncing ball on sinusoidally oscillating surface and explore the similarity between dynamics of the standard chaoticmap and bouncing ball dynamics. Then we investigated the discrete LQR optimal control technique to the control of chaotic system. The investigated design method is conceptually simple and computationally efficient. The effectiveness of the design method is demonstrated by simulation results.

UR - http://www.scopus.com/inward/record.url?scp=85012961087&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85012961087&partnerID=8YFLogxK

U2 - 10.1080/02286203.2016.1142275

DO - 10.1080/02286203.2016.1142275

M3 - Article

VL - 35

SP - 104

EP - 112

JO - International Journal of Modelling and Simulation

JF - International Journal of Modelling and Simulation

SN - 0228-6203

IS - 3-4

ER -