Intelligent switching adaptive control for uncertain nonlinear dynamical systems

I. Hsum Li, Lian Wang Lee*, Hsin Han Chiang, Pin Cheng Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


In this paper, we aim at proposing a switching adaptive control scheme using a Hopfield-based dynamic neural network (SACHNN) for nonlinear systems with external disturbances. In our proposed scheme, an auxiliary direct adaptive controller (DAC) ensures the system stability when the indirect adaptive controller (IAC) is failed; that is, g(x) approaches to zero, where g(x) is the denominator of an indirect adaptive control law. The IAC's limitation of g(x)>ε then can be solved by simply switching the IAC to the DAC, where ∈ is a positive desired value. The Hopfield dynamic neural network (HDNN) is used to not only design DAC but also approximate the unknown plant nonlinearities in IAC design. The designed simple structure of HDNN keeps the tracking performance well and also makes the practical implementation much easier because of the use of less and fixed number of neurons.

Original languageEnglish
Pages (from-to)638-654
Number of pages17
JournalApplied Soft Computing Journal
Publication statusPublished - 2015 Jun 20
Externally publishedYes


  • Adaptive control
  • Hopfield dynamic neural network
  • Switching control

ASJC Scopus subject areas

  • Software


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