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- W1556874954 abstract "A new controller scheme is introduced for unknown nonlinear dynamical processes that are modelled by an operating point neurofuzzy system. A neurofuzzy state space model of controllable form is initially constructed, based on a neurofuzzy design and model construction algorithm for nonlinear dynamical process, followed by a controller design based on closed loop pole assignment that ensures the system stability under some mild assumptions. This intelligent controller approach also includes a generalised Kalman filtering algorithm with coloured noise, based on the neurofuzzy state space model, to obtain an optimal state vector estimation for use in the state feedback stabilisation. The application of the algorithm to typical output tracking problem is used to demonstrate the applications of this new approach to intelligent control." @default.
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- W1556874954 date "2001-08-01" @default.
- W1556874954 modified "2023-10-03" @default.
- W1556874954 title "Neurofuzzy State Space Modelling and control Using Kalman Filtering State Feedback with Coloured Noise" @default.
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- W1556874954 doi "https://doi.org/10.1016/s1474-6670(17)41662-4" @default.
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