Sampled Data Sliding Mode Control of Magnetic Levitation System Using Extended Kalman Filter Estimator

In this paper, A Sliding Mode Control of Magnetic Levitation system for sampled data output feedback configuration is presented. Both regulation and tracking problems are considered. As all states are not available while control scheme is implemented on real time systems or a noisy output data is obtained because of sensor noise at the plant's output. For this purpose Extended Kalman Filter based estimator is employed to estimate the noise free and unknown states of plant. The control system is also tested under parametric perturbations/uncertainties and external disturbance to prove its robustness. Computer simulations show robust performance of control system.

[1]  Dragan Nesic,et al.  A framework for stabilization of nonlinear sampled-data systems based on their approximate discrete-time models , 2004, IEEE Transactions on Automatic Control.

[2]  Ali Saberi,et al.  Generalized output regulation for linear systems , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[3]  Li Qiu,et al.  Best Achievable Tracking Performance in Sampled-Data Systems via LTI Controllers , 2008, IEEE Transactions on Automatic Control.

[4]  Zi-Jiang Yang,et al.  Adaptive robust nonlinear control of a magnetic levitation system via DSC technique , 2001, Autom..

[5]  Ali Charara,et al.  Nonlinear control of a magnetic levitation system without premagnetization , 1996, IEEE Trans. Control. Syst. Technol..

[6]  C. M. Liaw,et al.  H∞ 2DOF control for the motion of a magnetic suspension positioning stage driven by inverter-fed linear motor , 2003 .

[7]  A. Ersak,et al.  State estimation of induction motor using unscented Kalman filter , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[8]  Zi-Jiang Yang,et al.  Adaptive robust nonlinear control of a magnetic levitation system via DSC technique , 2004 .

[9]  Dina Shona Laila,et al.  Design and analysis of nonlinear sampled data control systems , 2003 .

[10]  M. Jalili-Kharaajoo Robust variable structure control applied to voltage-controlled magnetic levitation systems , 2004, 2nd IEEE International Conference on Industrial Informatics, 2004. INDIN '04. 2004.

[11]  Simon Haykin,et al.  Adaptive Filter Theory 4th Edition , 2002 .

[12]  Celso J. Munaro,et al.  A design methodology of tracking controllers for magnetic levitation systems , 2001, Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01) (Cat. No.01CH37204).

[13]  Jin-Ho Seo,et al.  Design and analysis of the nonlinear feedback linearizing control for an electromagnetic suspension system , 1996, IEEE Trans. Control. Syst. Technol..

[14]  Ned Mohan,et al.  Design and implementation of an extended Kalman filter for the state estimation of a permanent magnet synchronous motor , 1991 .

[15]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[16]  Greg Welch,et al.  An Introduction to Kalman Filter , 1995, SIGGRAPH 2001.