This paper presents the design and implementation of a Switched Fractional Order Model Reference Adaptive Controller (SFOMRAC) for an Automatic Voltage Regulator (AVR). Given the complexity of the tuning process, the&nbsp;fractional orders, adaptive gains and switching times of the controller parameters adaptive laws are tunned offline, using Particle Swarm Optimization (PSO). The functional to be optimized contains not only parameters of the AVR response but also the control energy. Also, different weighting factors are used for the elements of the objective function, in order to make a fine tuning considering not only the system behavior but also the control energy used. The obtained controllers are compared to non switched Integer Order Model Reference Adaptive Controller (IOMRAC) and non switched Fractional Order Model Reference Adaptive Controller (FOMRAC) proposed previously for this process and also tuned in this work using the same procedure than for SFOMRAC.The results showed that if&nbsp;optimization algorithms are used to tune the controller parameters, SFOMRAC schemes can be found such that the controlled system has lower overshoot&nbsp;and lower settling time than the equivalent non switched strategies FOMRAC and IOMRAC, also with a control energy equal or not significantly higher than used in these schemes. Finally, results also showed that optimized SFOMRAC are not necessarily switched for every parameter adaptive law, but they can be a combination of switched and non switched adaptive laws.&nbsp;

Switched Fractional Order Model Reference Adaptive Control for an Automatic Voltage Regulator

Paper Proceedings: https://asmedigitalcollection.asme.org/IDETC-CIE/IDETC-CIE2021/volume/85369

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