Design of Metaheuristically Supervised Linear ADRC for a Magnetic Levitation System Control

A magnetic levitation system exhibits features of frictionless motion, low maintenance, and environmental isolation along with characteristics like chaos, uncertainty, multiple disturbances, and is highly nonlinear. These characteristics require a controller that doesn’t depend on a precise mathematical model, improves stability, dynamic response, and is robust against disturbances. Hence a linear active disturbance rejection controller (LADRC) is introduced into the system. A metaheuristic algorithm called cuckoo search has been used to fine-tune the parameters of LADRC, offering optimal solution with strong global search capabilities. To analyze the effectiveness of the proposed intelligent controller LADRC using cuckoo search is compared with a traditional PID controller based on their dynamic response and tracking performance. The analysis showed that LADRC with cuckoo search algorithm had a better tracking performance and dynamic response.