Recursive identification and adaptive prediction in linear stochastic systems
SIAM Journal on Control and Optimization
Convergence and logarithm laws of self-tuning regulators
Automatica (Journal of IFAC)
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Adaptive Filtering Prediction and Control
Adaptive Filtering Prediction and Control
Combined parameter and output estimation of dual-rate systems using an auxiliary model
Automatica (Journal of IFAC)
Identification of Hammerstein nonlinear ARMAX systems
Automatica (Journal of IFAC)
Hierarchical gradient-based identification of multivariable discrete-time systems
Automatica (Journal of IFAC)
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This paper develops a hierarchical extended stochastic gradient identification algorithms for MIMO ARMAX-like systems to deal with colored noises based on the hierarchical identification principle. The convergence performance of such algorithms is studied in detail; in particular, conditions for parameter estimation errors to converge to zero are established, which include persistent excitation of the extended information vectors and strict positive realness of the noise models. Finally, the proposed algorithms are tested on an example to show their advantages and effectiveness.