Unscented Kalman Filter in Adaptive Neural Model-based Predictive Control
نویسندگان
چکیده
An adaptive model-based predictive control scheme is proposed for non-linear systems. This methodology exploits the non-linear modelling capabilities of nonlinear state-space neural networks and the online weights adjustment by means of an unscented Kalman filter. Results from experiments show evidences on its good tracking performance even when the system’s dynamics change.
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