DESIGNING OF A MRAC-FUZZY WITH PD FEEDBACK FOR MARGINALLY STABLE SECOND-ORDER SYSTEM WITH DEAD TIME

Saibal  Manna; Deepak  Kumar Singh; Ashok  Kumar Akella

Authors

Saibal Manna Electrical Engineering Department, National Institute of Technology Jamshedpur, Jharkhand, 831014, India.
Deepak Kumar Singh Electrical Engineering Department, National Institute of Technology Jamshedpur, Jharkhand, 831014, India.
Ashok Kumar Akella Electrical Engineering Department, National Institute of Technology Jamshedpur, Jharkhand, 831014, India.

Keywords:

Lyapunov, Marginally stable, MRAC, MRAC-Fuzzy, MRAC-Fuzzy-PD, Second Order Process

Abstract

The performance of a traditional controller with fixed tuning is unsatisfactory for timevaryingsystems. This drawback can be resolved by using adaptive controllers, as theircontrol policies can be changed in accordance with change in process dynamics. Thisresearch presents a model reference adaptive controller (MRAC) for controlling anonlinear system through a network, subject to a time delay caused by a variablenetwork. In MRAC, the controller outcome relies on the difference between actualprocess and reference model outcome with fixed adaptation gain. The desiredrequirements of the process outcome are given as a reference model. The main aim isto find further improvement of the traditional MRAC method and provide more accuratecontrol to the marginally stable second-order process with dead time (MS-SOPDT) andminimize drawbacks of the traditional MRAC method. Here, a novel MRAC-Fuzzybased PD feedback (MRAC-FPD) control technique is proposed for MS-SOPDT. Thispaper also provides a comparative analysis of different MRAC strategies like MRACMIT,MRAC-PD, MRAC-Lyapunov, MRAC-Lyapunov-PD, MRAC-Fuzzy. Compare toother techniques, the proposed MRAC-Fuzzy-PD gives better response. This controlleroffers improved set point tracking with fewer oscillations and fast response. This factis also verified by the use of different performance indices such as integral timeabsolute error (ITAE), integral square error (ISE), and integral absolute error (IAE)under closed-loop conditions. These methods are demonstrated with the help ofMATLAB/Simulink.

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