DC Motor Speed Control Using Fractional Order Controllers Comparison Through Parametric Uncertainty

Controlling the speed of a DC motor is of paramount importance for obtaining accurate and efficient rotation control,especially in a wide range of industrial applications.Therefore,a variety of conventional controller techniques are employed for this purpose in accordance with the requirements of systems like PID,FOC,and FOSMC,well-known controllers.Each of them has perks as well as drawbacks to their use in industries.In this thesis,presented a novel fractional-order sliding-mode controller with parametric identification technique to control the rotational speed of a dc motor.The approach allows for the visualization of the consequences of unmolded dynamics and parametric uncertainty.The Lyapunov theorem is being used to maintains the stability of the system,which is defined using fractional calculus.MATLAB will be used to do the required simulations.The mathematical modeling of the DC motor system using a state-space method,taking into account the mechanical and electrical dynamics of the motor as well as the uncertainties in the system parameters,is the first step in the research.The system’s ability was further enhanced by the parameter identification method because the PID or FOSMC alone is insufficient to increase the robustness to reduce the chattering and oscillation in the system.In the next step,system’s ability was further enhanced by control system with the added benefit of FOC for efficient motor speed control,SMC for enhanced robustness,and PI control to minimize steady-state error and enhance transient response.Check the performance of model under load and without load situations.After monitoring and analyzing the results of the(PID),(FOSMC)(FOSMCI)controller.The results show outstanding speed control accuracy,robustness,and transient responsiveness of Proposed model.By combining the benefits of fractional order control(FOC),sliding mode control(SMC),and the parametric identification(PI)technique,it is possible to successfully reduce chattering,enhance resilience,and reduce steady-state error.findings of the research support the ongoing efforts to create cutting-edge control systems for industrial automation and robotics.