MADALINE Neural Network for Parameter Estimation of LTI MIMO Systems

In this paper, the Multi-AD Aptive LINear Element (MADA LINE) neural network was generalized for On-line System identification of linear time-invariant (LTI) Multi-Input Multi-Output (MIMO) systems. Based on the input output polynomial model which can be easily transformed into the row canonical state space model, Tapped delay line are introduced, so the MADALINE becomes recurrent in nature and thus is suitable for parameter estimation of such systems. The MADALINE can then be setup under the assumption that the system structure is known in advance. The estimated parameters are obtained as the weights of trained individual neurons of the MADALINE. The method is implemented in MATLAB and simulation study was then performed on a few well known examples. Simulation results show that the algorithms offer satisfactory performance. This work is extended from our previous work on Single Input Single Output such systems ([16]).