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Moncrief-O’Donnell Chair, UTA Research Institute (UTARI) The University of Texas at Arlington, USA and F.L. Lewis, NAI Talk available online at http://www.UTA.edu/UTARI/acs Summary of Optimal Control Design Supported by : China Qian Ren Program, NEU China Education Ministry Project 111 (No.B08015) NSF, ONR Qian Ren Consulting Professor, State Key Laboratory of Synthetical Automation for Process Industries Northeastern University, Shenyang, China

optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve

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Page 1: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve

Moncrief-O’Donnell Chair, UTA Research Institute (UTARI)The University of Texas at Arlington, USA

and

F.L. Lewis, NAI

Talk available online at http://www.UTA.edu/UTARI/acs

Summary of Optimal Control DesignSupported by :China Qian Ren Program, NEUChina Education Ministry Project 111 (No.B08015)NSF, ONR

Qian Ren Consulting Professor, State Key Laboratory of SyntheticalAutomation for Process Industries

Northeastern University, Shenyang, China

Page 2: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve
Page 3: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve

Static Optimization

min ( , )u

L x u

Subject to constraint ( , ) 0f x u

Solution. Define Hamiltonian function

( , , ) ( , ) ( . )TH x u L x u f x u

Adjoin constraints to the performance index using Lagrange multiplier

Page 4: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve

Discrete-time Nonlinear Optimal Control

Page 5: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve
Page 6: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve

Steady-State Discrete-Time LQR

SOLUTION

Page 7: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve
Page 8: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve
Page 9: optimal control summary - University of Texas at Arlington 05 NEU short course/optimal control summary.pdf · Select design parameter weighting matrices Q = QT 2 0 R = RT > 0 Solve

BuAxx u Kx

02

1 dtRuuQxxJ TT

Steady-State Continuous-Time LQR

System

Select input

To minimize the Performance Index

01 PBPBRQPAPA TT