Efficient parameterization for grey-box model identification of complex physical systems
System Identification, Volume # 14 | Part# 1
Authors
M. Blanke; M. Knudsen
Identifier
10.3182/20060329-3-AU-2901.00049
Index Terms
grey-box identification,marine systems,parameter inter-depence
Abstract
Grey box model identification preserves known physical structures in a model but with limits to the possible excitation, all parameters are rarely identifiable, and different parametrizations give significantly different model quality. Convenient methods to show which parameterizations are the better would be very useful. This paper shows how we can assess the parameter interdependence and model quality. Hessian matrix decomposition is employed to show linear dependencies between variables and to put a quality tag on different parameterizations. The method determines parameter relations that need be constrained to achieve satisfactory convergence. Identification of nonlinear models for a ship illustrate the concept.
References
[1] M. Blanke and A. Christensen. Rudder-roll damping
autopilot robustness to sway-yaw-roll couplings.
In Proc. 10th Ship Control Systems
Symposium, Ottawa, Canada, October 1993.
[2] M. Blanke and A. G. Jensen. Dynamic properties
of vessels with low metacentric height. Transactions
of the Institution of Measurement and
Control (UK), 1997.
[3] M. S. Chislett. Manoeuvring model parameter
estimates for standard flex 300 - private communication.
Technical report, Danish Maritime
Institute, March 1985.
[4] M. S. Chislett. The addition of heel-roll servo
mechanism to the dmi horizontal planar motion
mechanism. In Proc. MARSIM and ICSM,
Tokyo, 1990.
[5] Graham C. Goodwin and Robert L. Payne. Dynamic
System Identification. Academic Press,
1977.
[6] M. Knudsen. A sensitivity approach for estimation
of physical parameters. In 10th IFAC
Symposium on System Identification, volume 2
p. 231, Copenhagen, Denmark, 1994.
[7] L. Ljung. System Identification - Theory for the
User, 2nd edition. Prentice Hall Int., 1999.
[8] Ralf L. M. Peeters and Bernard Hanzon. Identifiability
of homogeneous systems using the state
isomorphism approach. Automatica, 40(3): 513-
529, 2005.
[9] Tristan Perez. Ship Motion Control - course
keeping and roll stabilisation using rudder and
fins. Advances in Industrial Control. Springer,
2005.
[10] Eric Walter and Luc Pronzato. On the identifiability
and distinguishability of nonlinear parametric
models. Mathematics and Computers in
Simulation, 32(2): 125-134, 1996.
[11] Eric Walter and Lue Pronzato. Identification
of Parametric Models form Experimental Data.
Springer, 1997.
[12] W. W. Zhou and M. Blanke. Identification of a
class of nonlinear state space models using rpe
techniques. IEEE Transactions of Automatic
Control., Vol. 34. No. 3: 312-316, 1989.
