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An Input to State Stability Approach for Evaluation of Nonlinear Control Loops with Linear Plant Model

  • Peter Benes
  • Ivo Bukovsky
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 765)

Abstract

This paper introduces a novel ISS stability evaluation for a LNU based HONU-MRAC control loop where an LNU serves as a plant and a HONU as a non-linear polynomial feedback controller. Till now, LNUs have proven their advantages as computationally efficient and effective approximators, further optimisers of linear and weakly non-linear dynamic systems. Due to the fundamental construction of an HONU-MRAC control loop featuring analogies with discrete-time non-linear dynamic models, two novel state space representations of the whole LNU based HONU-MRAC control loop are presented. Backboned by the presented state space forms, the ISS stability evaluation is derived and verified with theories of bounded-input-bounded-state (BIBS) and Lyapunov stability on a practical non-linear system example.

Keywords

Bounded-Input-Bounded-Output (BIBO) Bounded-Input-Bounded-State (BIBS) Higher-Order Neural Units (HONUs) Input-to-State Stability (ISS) Higher Order Neural Unit (HONU) Linear Neural Unit (LNU) Model Reference Adaptive Control (MRAC) 

Notes

Acknowledgements

Authors acknowledges support from the EU Operational Programme Research, Development and Education, and from the Center of Advanced Aerospace Technology (CZ.02.1.01/0.0/0.0/16_019/0000826)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Instrumentation and Control EngineeringCzech Technical University in PraguePragueCzech Republic
  2. 2.Department of Mechanics, Biomechanics and Mechatronics, Center of Advanced Aerospace TechnologyCzech Technical University in PraguePragueCzech Republic

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