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- W2198240848 abstract "This paper proposes a new scheme of on-line identification for feedforward (FF) learning control of an unknown nonlinear multi-input multi-output (MIMO) plant free of zero dynamics. This is achieved by constructing a FF controller consisting of a bank of linear approximation models for various operating points, which are discretized and called scheduler. Conventional schemes used piecewise constant/linear interpolation techniques to address the discretization. However, the accuracy of response shaping was insufficient. To improve the performance, we propose to take a basis function approach to tune the parameter of the FF controller. To verify the effectiveness of the proposed scheme, numerical simulation is carried out using the motion equation of a two-link manipulator." @default.
- W2198240848 created "2016-06-24" @default.
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- W2198240848 date "2015-10-01" @default.
- W2198240848 modified "2023-09-26" @default.
- W2198240848 title "A basis function approach to scheduled locally weighted regression for on-line modeling of nonlinear dynamical systems" @default.
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- W2198240848 doi "https://doi.org/10.1109/iccas.2015.7364874" @default.
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