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ABSTRACT
A new approach to the parameter identification of nonlinear dynamic systems using cascade models with nonlinear dynamic, linear dynamic and nonlinear static blocks is presented. Application of the key-term separation principle provides special expressions for the corresponding nonlinear model description that are linear in parameters. A least-squares-based iterative technique is proposed allowing estimation of all the model parameters based on measured input/output data. Illustrative examples of nonlinear cascade systems identification with input backlash and nonlinear static output characteristics are included.
Acknowledgements
The author gratefully acknowledges financial support from the Slovak Scientific Grant Agency (VEGA).
Disclosure statement
No potential conflict of interest was reported by the author.