Optimal and Suboptimal Control Design Strategy for the Maglev System

The magnetic levitation (Maglev) system is the exceedingly unstable and nonlinear system. The magnetic Levitation has been a desirous area of exploration for utilization, especially in the scope of automotive where low losses due to friction and low energy consumption are an important idea. The Maglev system has become a large effective technology in the intensity of the mass transportation system due to its friction-free motion. These systems have nonlinear dynamics that are open-loop unstable and it is inherently a nonlinear system, which required the implementation of a controller for its stabilization and position-tracking. Its controller design is a challenging problem. The control design process of optimal control technique for large scale systems is very difficult because of main demerits of optimal control principle which demands feedback completely from state variables, which are exhibited to depict the dynamics of the system (Maglev). A practically identical execution basis has been created, which is to be utilized related to the improved models to determine the suboptimal controllers. The technique created is additionally valuable when few state variables don't exist for metering and feedback. This paper presented, an innovative approach for suboptimal controller design using measurable states for feedback is proposed. The Balance truncation method used for (MOR) model order reduction by considering the controller parameters. The MOR technique offers a stage to a simple understanding of the main system. It also supplies an effortless dynamic for simple treatment and control characteristic. Design of the suboptimal controllers are more cost effective and easy to hardware necessity is considerably decreased. The Simulation results have been presented to compare the impact of the two Controller in terms of their ability to respond to step inputs by the proposed method and the optimal control approach.