Identification of a Class of MIMO Nonlinear Continuous-time Systems withObservable States Using Driving Signal
一类MIMO状态可测的非线性连续系统的激励辨识方法

We propose an identification approach for a type of MIMO nonlinear continuous-time systems with observable states using driving signals.The driving signal is Gaussion white noise, the state outputs are sampled evenly.The maximum likelihood estimates of the model parameters are derived by using the Gir- sanov theorem.The numerical simulations illustrate the effi- ciency of the estimates and the NNR phenomenon of coupling multi-variable appears in the numerical simulations.A step-type identification algorithm is suggested at the end.