Open loop dynamic trajectory generator for a fuzzy gain scheduler |
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| Affiliation: | 1. Department of Mechanical Engineering, University of Chile, Santiago 8370448, Chile;2. Institute for Computational Engineering, Faculty of Science, Technology and Communication, University of Luxembourg, Luxembourg;3. Department of Civil and Environmental Engineering, University of Waterloo, ON, Canada;4. Cardiff University, Institute of Mechanics and Advanced Materials, School of Engineering, College of Physical Sciences and Engineering, UK;5. University of Western Australia, Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, Australia |
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| Abstract: | This paper presents a dynamic trajectory generator for a nonlinear system to be controlled by a fuzzy gain scheduler composed of a set of local linear Takagi–Sugeno (TS) fuzzy controllers. The local control laws are designed for the error system including the desired state and the corresponding desired control input. The task of the open loop dynamic trajectory generator is the generation of a sequence of control inputs along a predefined dynamic trajectory of the nominal nonlinear system. While the desired state is normally given, the corresponding desired control input may not always be computable in an explicit or unique way. With the proposed method the desired control input is approximated by an inverse fuzzy model of the nominal system. The model is built on the basis of a combination of c-elliptotype and Gustafson–Kessel clustering and a subsequent identification of local linear and affine TS models. In a next one-step ahead optimization loop the approximated control input is corrected by an analytical forward model of the nominal system. |
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