Some Investigations on the Design and Implementation of Fractional Order Control System

Abstract

This thesis investigates the application of fractional order control methodology in the design of control systems for linear and nonlinear systems. The fractional-order control algorithm like FOPID, Adaptive Controller, Model Reference Adaptive Control (MRAC), Fractional Order MRAC(FO-MRAC), Fractional order optimal control (FOCP ), etc have been explored for the given plant. The effectiveness of soft computing technique based adaptation mechanisms for MRAC is also presented in the present work. Further, an identification technique has been proposed to find out the fractional-order transfer of the given plant. Role of the artificial intelligence-based algorithm and metaheuristic based algorithm is also explored. Since the fractional-order operator itself represents the infinite-dimensional system, it is necessary to find a suitable approximation of the fractional-order operator. A lot of research work has been carried out approximate the fractional-order operator in finite-dimensional space. Out of the many available methods and combinations available, it has been necessary to find out the appropriate approximation method for the given system. A comparative analysis based study has been carried out to select a suitable method to approximate the fractional-order operator. Using this method, all the related simulations and hardware implementation has been carried out. Most of the model-based control strategies are failed in the practical environment due to inherent nonlinearity and unknown dynamics in the system, Fractional-order modelling overcome this disadvantage. Idea is to take benefit of fractional order modelling for accurate control of the fractional-order system. A practical methodology has been suggested for the identification and control of the fractional-order control system. Results are presented, analyzed and compared for applied strategies With results, it has been observed that to fractional-order model fits better than the integer-order model. Further, it has been observed that fractional-order control algorithms outperform the integer-order control algorithms. Fractional order optimal control problem is not addressed in great depth so far. A method has been suggested to take advantage of FOCP in control of integer order dynamics and fractional-order dynamics. Results are validated on two setups. The first set up is DC motor setup and the second setup is the auto-balance robot setup. It has come out as the best of all applied strategies with improved results. The overall stability of the proposed system is proven using simple control techniques.