Smith predictor based control of fractional order systems with time delay

The Smith predictor is a widely adopted control strategy for systems with time delays, providing improved stability and performance by compensating for the negative effects of delay. This thesis focuses on the design of Smith predictor based controllers for fractional order systems characterized by time delay. Fractional order systems, which have the ability to model real-world systems more accurately than integer-order systems, present challenges in control design due to their non-integer dynamics. The proposed approach combines the capabilities of the Smith predictor with the flexible modelling power of fractional calculus to achieve superior control performance. Analysis is conducted using a hybrid optimization algorithm that combines the advantages of Firefly and Genetic Algorithm to determine the controller parameters. Simulation studies for various fractional order systems with time delays are presented to demonstrate the effectiveness of the proposed method. The results reveal significant improvements in system stability, time response, and robustness compared to traditional methods, making this approach a promising solution for advanced control applications.