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Model Predictive Control of the Two Rotor Aero-Dynamical System Using State Space Neural Networks with Delays

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Intelligent Systems in Technical and Medical Diagnostics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 230))

Abstract

This paper deals with the application of state space neural network model with delays to design a model predictive control for a laboratory stand of the Two Rotor Aero-dynamical system. The work describes approach based on the so-called instantaneous linearisation of the already trained nonlinear state space model of the system. With obtained linear model it is possible to derive a vector of future controls based on the minimisation of the cost function within one optimisation window. Repeating procedure in each step of simulation and applying the obtained control signal allows for efficiently control of the nonlinear systems. All data used in experiments is obtain from the real-time laboratory stand which is working in Matlab/Simulink RTW environment.

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Correspondence to Andrzej Czajkowski .

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Czajkowski, A., Patan, K. (2014). Model Predictive Control of the Two Rotor Aero-Dynamical System Using State Space Neural Networks with Delays. In: Korbicz, J., Kowal, M. (eds) Intelligent Systems in Technical and Medical Diagnostics. Advances in Intelligent Systems and Computing, vol 230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39881-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-39881-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39880-3

  • Online ISBN: 978-3-642-39881-0

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