Gradient-based and least-squares-based iterative estimation algorithms for multi-input multi-output systems:

摘要: System modelling is important for studying the motion laws of dynamical systems. Parameters system models can be estimated through identification methods from measurement data. This paper develops a gradient-based and least-squares-based iterative estimation algorithms to estimate parameters multi-input multi-output (MIMO) with coloured auto-regressive moving average (ARMA) noise input–output data, based on gradient search least-squares principles, respectively. The key replace unknown terms residuals contained in information vector their corresponding estimates at previous iteration. simulation test results indicate that proposed are effective.