DIRECT ADAPTIVE NEURO CONTROL OF ELECTROMAGNETIC SUSPENSION (EMS) SYSTEM Anan Suebsomran Department of Teacher Training in Mechanical Engineering, Faculty of Technical Education The objective of this research presents the controller design of magnetic levitation application. The highly nonlinear electromagnetic suspension (EMS) system is hardly and limited the system control subjected to prescribed stability of system. Due to the nonlinear dynamics of system, the linearization of the nonlinear EMS plant is obtained with linear model by using linear approximations. An attraction force about the prescribed nominal operating point of current and air-gap position is chosen for linearization. Linear state feedback control, direct adaptive neuro control, and hybrid of linear state feedback and direct adaptive neuro control are applied for controlling nonlinear dynamics and parametric uncertainty of plant system. For the direct adaptive neuro control, radial basis function neural network (RBFNN) employs to approximate the nonlinearity and uncertainty of electromagnetic suspension (EMS) plant due to unstructured modelling. The system stability and adaptation is proofed by using Lyapunov’s method. The results of proposed control performance are clearly explained comparatively in practical implementation by experiments. King Mongkut’s University of Technology North Bangkok OBJECTIVE METHODOLOGY System modelling of electromagnetic suspension (EMS) system Linearization of a nonlinear system Controller design based on and a hybrid of linear state feedback and direct adaptive neuro control Simulation verification Experimentation by performance comparison of proposed control and separated control method such as state feedback, direct neuro adaptive control Conclusion Dynamic model of a single axis EMS hhh The proposed control of a nonlinear electromagnetic syspension (EMS) system is effectively for applied to control the air-gap positioning of EMS system, especially in ground transportation, magnetic bearing or frictionless applications. Controller Design Figure 2: Proposed Control of EMS system GUIDELINES FOR THE INNOVATION AcknowledgementThis research work is financially supported by Office of the Higher Education Commission, and King Mongkut's University of Technology North Bangkok (contract no. 2554A ).. Contact: Research Center of Intelligent Machines and Robotics (iMR), Science and Technology Research Institue, King Mongkut’s University of Technology North Bangkok, Thailand; Figure 1: System model of EMS system Figure 3: Performance comparison of control design system of EMS system Conclusion Electromagnetic suspension (EMS) system significantly applies in advanced technology such as ground transportation, magnetic bearing and other applications. This research is proposed the control design of a nonlinear electromagnetic suspension (EMS) system. Linearization approximation around nominal operating point with desirable operating air gap position has been done. The nonlinear dynamics and inaccuracy of developed system is affected by unstructured modeling. Then direct adaptive neuro control is proposed to overcome such problems. In conclusion the system performance of linear state feedback control and direct adaptive neuro control can be applied for controlling the nonlinear electromagnetic suspension (EMS) system as shown in experiment. By means of comparison performance of control, we can conclude that the hybrid control of linear state feedback and direct adaptive neuro control yields the better performance. The other control schemes, linear state feedback and direct adaptive neuro control, are lower control performance than the hybrid control system, even though there are stable for control objective. The system stability and adaptation are guarantee by using Lyapunov’s function candidate. The proposed control performance is robustly stable with system nonlinearity. Results