[PDF] MOOSE MOdel based Optimal input Signal dEsign Toolbox

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CONTACT INFORMATION

MOOSE2

MO del based Optimal input Signal dEsign Toolbox (version 2: function- and YALMIP-based)

Mariette Annergren

PhD Student

mariette.annergren@ee.kth.se

Christian A. Larsson

Development Engineer at Scania CV AB

christian.y.larsson@scania.com (work done while post-doc at KTH)

Bo Wahlberg

Professor

bo.wahlberg@ee.kth.se

Håkan Hjalmarsson

Professor

hakan.hjalmarsson@ee.kth.se

ACCESS and Automatic Control Lab

KTH Royal Institute of Technology

Stockholm, Sweden

MOOSE2

www.kth.se/moose

Mariette Annergren

Christian A. Larsson

MOOSE2 is a MATLAB toolbox for solving

applications-oriented input design problems.

MOOSE2 designs the spectrum of the input signal

used in the identification experiments.

Key features

MATLAB-based

Solves optimization

problems via YALMIP

Function-based interface,

including dedicated functions for

Application constraints

Quality constraints

Spectrum constraints

Input design

Objective:

Find input spectrum that

minimizes experiment cost

Constraint:

Guarantee that application

and quality constraints on the model are satisfied along with any spectra constraints

MOOSE2 example

y e u

Minimize input variance

Satisfy application constraint

FIR input spectrum with 20 lags

minimize

E{ݑ

subject to ߝ

0.95ك

100
(߱)൒0,߱ ׊ % SETUP THE SYSTEM AND MODEL theta = [10 -9];

Ts = 1;

r_e = 1; model = idpoly(1,theta,1,1,1,r_e,Ts); % INPUT DESIGN USING MOOSE2 problem = oidProblem(model,200,'FIR',20); problem.constraints{1} = optH = solve(problem,[1 0 0]); % GENERATE INPUT SIGNAL u = lsim(optH,randn(200,1)); www.kth.se/moose Future work:

Support for more spectrum types

Controller design

Support of signal constraints in time domain

Toolbox directly connected to optimization solver

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