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Polynomial Compensation of Odd Symmetric Nonlinear Actuators via Neural Network Modeling and Neural Network Describing Function

  • O. KuljacaEmail author
  • K. Horvat
  • J. Gadewadikar
  • B. Tare
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 313)

Abstract

Paper deals with polynomial compensation of odd symmetric nonlinear actuators. Most actuators are nonlinear sporting odd symmetric nonlinearities such as deadzone and saturation. One way of dealing with such actuators is to try to compensate for nonlinearities by polynomial representation of inverse nonlinearity. Compensated actuators can improve behavior of the system, but then arises the problem of stability analysis because compensated nonlinearity is now complex nonlinearity not described in common literature. One way of dealing with such problem is to perform stability analysis via describing function method. Paper describes the method for compensating nonlinearities, recording describing function and performing stability analysis.

Keywords

Neural network Polynomial compensation Odd symmetrical nonlinearities Compensated actuators 

Notes

Acknowledgment

Research was partially supported by HZZZ grant 09/193 Fuzzy Logic Adaptive Elastic Controller.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • O. Kuljaca
    • 1
    Email author
  • K. Horvat
    • 1
  • J. Gadewadikar
    • 2
  • B. Tare
    • 3
  1. 1.Control Engineering DepartmentBrodarski InstituteZagrebCroatia
  2. 2.Systems Research InstituteAlcorn State UniversityLormanUSA
  3. 3.Deloitte ConsultingNew YorkUSA

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