0
Journal of Dynamic Systems, Measurement, and Control | Volume 139 | Issue 9 | Technical Brief
Technical Brief

H∞ Optimal Controller Design With Closed-Loop Positive Real Constraints

[+] Author and Article Information
L. Hewing

Institute for Dynamic Systems and Control (IDSC),
ETH Zurich,
Zurich 8092, Switzerland
e-mail: lhewing@ethz.ch

S. Leonhardt, B. J. E. Misgeld

Philips Chair for Medical Information Technology (MedIT),
RWTH Aachen University,
Aachen 52074, Germany

P. Apkarian

Control Systems Department,
Onera,
Toulouse 31055, France

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 23, 2016; final manuscript received February 8, 2017; published online June 5, 2017. Assoc. Editor: Ryozo Nagamune.

J. Dyn. Sys., Meas., Control 139(9), 094502 (Jun 05, 2017) (8 pages) Paper No: DS-16-1413; doi: 10.1115/1.4036073 History: Received August 23, 2016; Revised February 08, 2017
Article
References
Figures
Tables

Positive real constraints on the closed-loop of linear systems guarantee stable interaction with arbitrary passive environments. Two such methods of H∞ optimal controller synthesis subject to a positive real constraint are presented and demonstrated on numerical examples. The first approach is based on an established multi-objective optimal control framework using linear matrix inequalities and is shown to be overly restrictive and ultimately infeasible. The second method employs a sector transformation to substitute the positive real constraint with an equivalent H∞ constraint. In two examples, this method is shown to be more reliable and displays little change in the achieved H∞ norm compared to the unconstrained design, making it a promising tool for passivity-based controller design.
FIGURES IN THIS ARTICLE
<>
Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

Multi-objective generalized plant configuration

+Multi-objective generalized plant configuration
View Large  |  Save Figure  |  Download Slide (.ppt)
Multi-objective generalized plant configuration
Grahic Jump Location
Fig. 2

Block diagram representation of the multi-objective Cayley transformation

+Block diagram representation of the multi-objective Cayley transformation
View Large  |  Save Figure  |  Download Slide (.ppt)
Block diagram representation of the multi-objective Cayley transformation
Grahic Jump Location
Fig. 3

Block diagram of a simple H∞ disturbance rejection problem

+Block diagram of a simple H∞ disturbance rejection problem
View Large  |  Save Figure  |  Download Slide (.ppt)
Block diagram of a simple H∞ disturbance rejection problem
Grahic Jump Location
Fig. 4

Singular value plot of the H∞ channel with different controllers

+Singular value plot of the H∞ channel with different controllers
View Large  |  Save Figure  |  Download Slide (.ppt)
Singular value plot of the H∞ channel with different controllers
Grahic Jump Location
Fig. 5

Bode plot of the closed-loop frequency response Tcl(jω)=y(jω)/d(jω)

+Bode plot of the closed-loop frequency response Tcl(jω)=y(jω)/d(jω)
View Large  |  Save Figure  |  Download Slide (.ppt)
Bode plot of the closed-loop frequency response Tcl(jω)=y(jω)/d(jω)
Grahic Jump Location
Fig. 6

Simple series elastic actuator (SEA) model consisting of motor inertia J, viscous friction coefficient b, and ideal spring constant k

+Simple series elastic actuator (SEA) model consisting of motor inertia J, viscous friction coefficient b, and ideal spring constant k
View Large  |  Save Figure  |  Download Slide (.ppt)
Simple series elastic actuator (SEA) model consisting of motor inertia J, viscous friction coefficient b, and ideal spring constant k
Grahic Jump Location
Fig. 7

Augmented plant for controller design of simple SEA

+Augmented plant for controller design of simple SEA
View Large  |  Save Figure  |  Download Slide (.ppt)
Augmented plant for controller design of simple SEA
Grahic Jump Location
Fig. 8

Nyquist plot of the impedance transfer function for simple SEA example with either classically designed H∞ controller or positive real constraint Cayley approach H∞ controller

+Nyquist plot of the impedance transfer function for simple SEA example with either classically designed H∞ controller or positive real constraint Cayley approach H∞ controller
View Large  |  Save Figure  |  Download Slide (.ppt)
Nyquist plot of the impedance transfer function for simple SEA example with either classically designed H∞ controller or positive real constraint Cayley approach H∞ controller
Grahic Jump Location
Fig. 10

Reference tracking step response for simple SEA example with either classically designed H∞ controller or positive real constraint Cayley approach H∞ controller

+Reference tracking step response for simple SEA example with either classically designed H∞ controller or positive real constraint Cayley approach H∞ controller
View Large  |  Save Figure  |  Download Slide (.ppt)
Reference tracking step response for simple SEA example with either classically designed H∞ controller or positive real constraint Cayley approach H∞ controller
Grahic Jump Location
Fig. 9

Bode plot of the controller transfer function for both classic H∞ controller and positive real constraint Cayley approach H∞ controller

+Bode plot of the controller transfer function for both classic H∞ controller and positive real constraint Cayley approach H∞ controller
View Large  |  Save Figure  |  Download Slide (.ppt)
Bode plot of the controller transfer function for both classic H∞ controller and positive real constraint Cayley approach H∞ controller

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Designing an Artificial Muscle Based on PID Controller and Tuned by Neural Network with a NN Identification of the Plant
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
Station Automation
Pipeline System Automation and Control> Chapter 3
New H∞ Controllers Design for Networked Control System with Disturbance Based on Asynchronous Dynamical System
International Conference on Advanced Computer Theory and Engineering (ICACTE 2009)
Design of Assembly Robot Controller Based on PROFI-BUS for Hubcap Gear-Box Pressure Assembling
Proceedings of the 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2010)
The Design of LQR and Fuzzy Logic Controller for a Thermal System with Large Time Delay
Proceedings of the 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2010)
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In