Identification of Dynamical Systems Using GMM with VQ Initialization
نویسندگان
چکیده
We are using Gaussian Mixture Models (GMM) as a tool to construct local mappings of nonlinear Multi-Input Multi-Output (MIMO) systems. In this work we combine the advantages of GMM with the Kalman filter. To improve the accuracy of the local linear mappings in a potentially large dimensional state space, we propose to initialize the GMM parameters with Vector Quantization (VQ) or its more parsimonious counterpart Growing Self-Organizing Maps (GSOM). The performance of the proposed modeling algorithms on simulated data obtained from a realistic aircraft model show improvements in both converge speed and accuracy.
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