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Al-Hadithi, Basil M. and Adánez García-Villaraco, José Miguel and Jiménez Avello, Agustín (2019). Takagi-Sugeno fuzzy incremental state model for optimal control of a ball and beam nonlinear model. In: "14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)", 13/05/2019-15/05/2019, Sevilla, España. ISBN 978-3-030-20054-1. pp. 533-543. https://doi.org/10.1007/978-3-030-20055-8_51.
Title: | Takagi-Sugeno fuzzy incremental state model for optimal control of a ball and beam nonlinear model |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) |
Event Dates: | 13/05/2019-15/05/2019 |
Event Location: | Sevilla, España |
Title of Book: | Advances in intelligent systems and computing |
Date: | May 2019 |
ISBN: | 978-3-030-20054-1 |
Volume: | 950 |
Subjects: | |
Freetext Keywords: | Ball and beam; Takagi-Sugeno; Incremental state model; Optimal control |
Faculty: | E.T.S.I. Diseño Industrial (UPM) |
Department: | Ingeniería Eléctrica, Electrónica Automática y Física Aplicada |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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The optimal control of a ball and beam by an approach based on Takagi-Sugeno incremental state model is proposed. The advantages of incremental state model in comparison with the non incremental one are that the control action cancels steady state errors, the affine terms disappear and incremental state solves the problem of computing the target state, choosing zero as an objective. A generalized version of Takagi-Sugeno identification method is applied. For an optimal control, Linear Quadratic Regulator and optimal state observer are used in each fuzzy rule. Simulation results over the ball and beam nonlinear model show a stable closed loop in the full range, zero steady state error and good transient response.
Type | Code | Acronym | Leader | Title |
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Government of Spain | DPI2017-86915-C3-3-R | COGDRIVE | Unspecified | Técnicas de inteligencia artificial y ayuda a la navegación autónoma = Cognition inspired navigation for autonomous driving |
Item ID: | 55515 |
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DC Identifier: | https://oa.upm.es/55515/ |
OAI Identifier: | oai:oa.upm.es:55515 |
DOI: | 10.1007/978-3-030-20055-8_51 |
Official URL: | https://link.springer.com/chapter/10.1007%2F978-3-030-20055-8_51 |
Deposited by: | Memoria Investigacion |
Deposited on: | 20 Jun 2019 08:35 |
Last Modified: | 31 Dec 2019 23:30 |