A Fuzzy-Based Modified Gain Adaptive Scheme for Model Reference Adaptive Control

  • A. K. Pal
  • Indrajit Naskar
  • Sampa Paul
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 701)


In this paper, a fuzzy-based adaptive scheme for model reference adaptive control (MRAC) is proposed. In MRAC, the choice of proper adaptive gain (γ) is a cumbersome job, and it is usually done by trial and error method. To eliminate this shortcoming, here fuzzy logic is incorporated in the control loop to tune the adaptive gain (γ). In design of model reference adaptive control, MIT rule is followed, where a cost function is defined as a function of error between the outputs of the plant and the reference model, and the controller parameters are adjusted in such a way so that this cost function is minimized. The experiments on the different second-order linear/nonlinear systems are illustrated to show the merits of the proposed fuzzy-based model reference adaptive control (FMRAC) scheme over the MRAC. The performances of the proposed control algorithms are evaluated and shown by means of simulation on MATLAB and Simulink.


Adaptive control Fuzzy control MIT rule Fuzzy-based MRAC Adaptation gain 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of AEIEHeritage Institute of TechnologyKolkataIndia

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