Excitation signal design for nonlinear dynamic systems with multiple inputs – A data distribution approach

Author:

Heinz Tim Oliver1,Nelles Oliver1

Affiliation:

1. Universität Siegen , Mess- und Regelungstechnik – Mechatronik, Department Maschinenbau , Paul-Bonatz-Str. 9-11 , D-57068 , Siegen , Germany

Abstract

Abstract A methodology to generate excitation signals that can be used for the identification of nonlinear dynamic systems is proposed. In contrast to traditional approaches which are based on specific signal types, the objective here is the homogeneous distribution of the data points in the input space of the model. A space-filling data distribution in the whole input space is a necessity for gathering information about the nonlinearities of the system and minimizes the risk of extrapolation. The methodology can be extended to multiple inputs with moderate increase in complexity which is a key feature for most real-world applications. The quality of the excitation signal is demonstrated with simulations and on a high pressure fuel supply system.

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference19 articles.

1. Wolf Baumann, Steffen Schaum, Karsten Roepke and Mirko Knaak, Excitation signals for nonlinear dynamic modeling of combustion engines, in: Proceedings of the 17th World Congress, The International Federation of Automatic Control, Seoul, Korea, 2008.

2. Liu Bo, Zhao Jun and Qian Jixin, Design and analysis of test signals for system identification, Computational Science – ICCS 2006, Springer, 2006, pp. 593–600.

3. George EP Box and R Daniel Meyer, An analysis for unreplicated fractional factorials, Technometrics 28 (1986), 11–18.10.1080/00401706.1986.10488093

4. Marco Cavazzuti, Optimization methods: from theory to design scientific and technological aspects in mechanics, Springer Science & Business Media, 2012.

5. Tobias Ebert, Torsten Fischer, Julian Belz, Tim Oliver Heinz, Geritt Kampmann and Oliver Nelles, Extended Deterministic Local Search Algorithm for Maximin Latin Hypercube Designs, in: Computational Intelligence, 2015 IEEE Symposium Series on, IEEE, pp. 375–382, 2015.

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