Abstract
ABSTRACTA 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.
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