GA-based modified adaptive fuzzy sliding mode controller for nonlinear systems

P. C. Chen, C. W. Chen, W. L. Chiang

Research output: Contribution to journalArticlepeer-review

102 Scopus citations


In this paper, the stability analysis of the GA-based adaptive fuzzy sliding model controller for a nonlinear system is presented. First, an uncertain and nonlinear plant for the tracking of a reference trajectory is well approximated and described via the reference model and the fuzzy model involving fuzzy logic control rules. Next, the difficulty in designing a fuzzy sliding mode controller (FSMC) capable of rapidly and efficiently controlling complex and nonlinear systems is how to select the most appropriate initial values for the parameter vector. The initial values of the consequent parameter vector are decided via the genetic algorithm. After this, a modified adaptive law can be adopted to find the best high-performance parameters for the fuzzy sliding model controller. The adaptive fuzzy sliding model controller is derived to simultaneously stabilize and control the system. The stability of the nonlinear system is ensured by the derivation of the stability criterion based upon Lyapunov's direct method. Finally, a numerical simulation is provided as an example to demonstrate the control methodology.

Original languageEnglish
Pages (from-to)5872-5879
Number of pages8
JournalExpert Systems with Applications
Issue number3 PART 2
StatePublished - Apr 2009


  • Genetic algorithm
  • Lyapunov direct method
  • Modified adaptive law


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