Design of Fuzzy-PID Controller Using Optimization Technique based Reduced Order Modelling

The design of a fuzzy-PID controller for Particle Swarm Optimization (PSO) and Greywolf Optimization (GWO) approaches is explored in this study. With these techniques, we can convert a higher order system into a lower order model. Higher order physical systems are typically too difficult to analyze, enabling the replacement of the higher order system(HOS) with a lower order model that has less complexity while keeping the original system essential characteristics. The original system is typically improved using reduce order modelling (ROM), which lowers the complexity of the controller design by reducing the number of control parameters. The simulation outcomes using different optimization techniques for ROM, including PSO and GWO, are then contrasted with those obtained using more conventional ROM techniques, such as Pole Clustering, Pade Approximation, and Routh Approximation. The development of a controller for the reduced model that can also be implemented to the initial HOS is the next step. Here, the gain settings of a PID controller are chosen using a fuzzy logic-based control technique.