A method for systematic improvement of stochastic grey-box models

Author:

Kristensen Niels Rode,Madsen Henrik,Jørgensen Sten Bay

Publisher

Elsevier BV

Subject

Computer Science Applications,General Chemical Engineering

Reference20 articles.

1. Allgöwer, F., & Zheng, A. (Eds.). (2000). Nonlinear model predictive control. In Progress in systems & control theory (Vol. 26). Switzerland: Birkhauser Verlag.

2. Åström, K. J. (1970). Introduction to stochastic control theory. New York, USA: Academic Press.

3. Bak, J., Madsen, H., & Nielsen, H. A. (1999). Goodness of fit of stochastic differential equations. In P. Linde, A. Holm (Eds.), Symposium i Anvendt Statistik. Copenhagen, Denmark: Copenhagen Business School.

4. Bohlin, T. (2001). A Grey-Box Process Identification Tool: Theory and Practice. Technical Report IR-S3-REG-0103, Department of Signals, Sensors and Systems, Royal Institute of Technology, Stockholm, Sweden.

5. Issues in nonlinear stochastic grey-box identification;Bohlin;International Journal of Adaptive Control and Signal Processing,1995

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