Filtering Identification.Part N:Filtering-Based Auxiliary-Model Hierarchical Generalized Extended Iterative Parameter Identification for Multivariable Output-Error ARMA-Like Systems
For multivariable output-error autoregressive moving average-like(M-OEARMA-like)models,this paper investigates and proposes filtered auxiliary-model hierarchical gener-alized extended gradient-based iterative identification methods,filtered auxiliary-model hier-archical multi-innovation generalized extended gradient-based iterative identification meth-ods,filtered auxiliary-model hierarchical generalized extended least squares-based iterative i-dentification methods,and filtered auxiliary-model hierarchical multi-innovation generalized extended least squares-based iterative identification methods by means of the filtering identi-fication idea and the hierarchical identification principle from available input-output data.These filtered auxiliary-model hierarchical generalized extended iterative identification meth-ods can be extended to other linear and nonlinear multivariable stochastic systems with col-ored noises.
parameter estimationiterative identificationauxiliary model identificationmulti-innovation identificationhierarchical identificationfiltering identificationleast squaresmultivariable system
万方数据
维普
