Sadhana

, Volume 25, Issue 2, pp 169–180

A hyperstable neural network for the modelling and control of nonlinear systems

Article

DOI: 10.1007/BF02703757

Cite this article as:
Warwick, K., Zhu, Q.M. & Ma, Z. Sadhana (2000) 25: 169. doi:10.1007/BF02703757

Abstract

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.

Keywords

Computer control neural networks nonlinear systems adaptive control 

Copyright information

© Printed in India 2000

Authors and Affiliations

  1. 1.Department of CyberneticsUniversity of ReadingWhiteknightsUK
  2. 2.Department of Mechanical and Electrical EngineeringAston UniversityBirminghamUK
  3. 3.Center for Engineering Research Technikon NatalDurbanSouth Africa