CDM Based Servo State Feedback Controller with Feedback Linearization for Magnetic Levitation Ball System

This paper explains the design of Servo State Feedback Controller and Feedback Linearization for Magnetic Levitation Ball System (MLBS). The system uses feedback linearization to change the nonlinear model of magnetic levitation ball system to the linear system. Servo state feedback controller controls the position of the ball. An integrator eliminates the steady state error in servo state feedback controller. The parameter of integral gain and state feedback gains is achieved from the concept of Coefficient Diagram Method (CDM). The CDM requires the controllable canonical form, because of that Matrix Transformation is needed. Hence, feedback linearization is applied first to the MLBS then converted to a controllable form by a transformation matrix. The simulation shows the system can follow the desired position and robust from the position disturbance. The uncertainty parameter of mass, inductance, and resistance of MLBS also being investigated in the simulation. Comparing CDM with another method such as Linear Quadratic Regulator (LQR) and Pole Placement, CDM can give better response, that is no overshoot but a quite fast response. The main advantage of CDM is it has a standard parameter to obtain controller’s parameter hence it can avoid trial and error.

[1]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[2]  G. Sotelo,et al.  A Full Scale Superconducting Magnetic Levitation (MagLev) Vehicle Operational Line , 2015, IEEE Transactions on Applied Superconductivity.

[3]  W. Marsden I and J , 2012 .

[4]  Manfredi Maggiore *,et al.  Modelling and control design for a magnetic levitation system , 2004 .

[5]  Muhammad Ahsan,et al.  Control of a magnetic levitation system using non-linear robust design tools , 2013, 2013 3rd IEEE International Conference on Computer, Control and Communication (IC4).

[6]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[7]  Jong-Min Lee,et al.  Design of magnetic levitation electromagnet for High Speed Maglev train , 2013, 2013 International Conference on Electrical Machines and Systems (ICEMS).

[8]  S. Manabe Coefficient Diagram Method , 1998 .

[9]  P. N. Paraskevopoulos,et al.  Modern Control Engineering , 2001 .

[10]  Mir Behrad Khamesee,et al.  Optimal motion control of magnetically levitated microrobot , 2010, 2010 IEEE International Conference on Automation Science and Engineering.

[11]  Huann-Keng Chiang,et al.  Integral backstepping sliding mode control of a magnetic ball suspension system , 2013, 2013 IEEE 10th International Conference on Power Electronics and Drive Systems (PEDS).

[12]  M. Osman Tokhi,et al.  Optimal control based LQR-feedback linearisation for magnetic levitation using improved spiral dynamic algorithm , 2015, 2015 20th International Conference on Methods and Models in Automation and Robotics (MMAR).

[13]  S. Manabe Importance of coefficient diagram in polynomial method , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[14]  Li Jie,et al.  Study on two feedback linearization control methods for the magnetic suspension system , 2015, 2015 34th Chinese Control Conference (CCC).

[15]  N. Magaji,et al.  Fuzzy logic controller for magnetic lévitation system , 2014, 2014 IEEE 6th International Conference on Adaptive Science & Technology (ICAST).

[16]  M. N. Uddin,et al.  Design and performance analysis of a magnetically levitated vertical axis wind turbine based axial flux PM generator , 2012, 2012 7th International Conference on Electrical and Computer Engineering.

[17]  M. Omizo,et al.  Modeling , 1983, Encyclopedic Dictionary of Archaeology.

[18]  Paolo Dario,et al.  Magnetic Levitation camera robot for endoscopic surgery , 2011, 2011 IEEE International Conference on Robotics and Automation.

[19]  M. O. Tokhi,et al.  Control of single axis magnetic levitation system using fuzzy logic control , 2015, 2015 Science and Information Conference (SAI).

[20]  Bidyadhar Subudhi,et al.  Discrete backstepping control of magnetic levitation system with a nonlinear state estimator , 2016, 2016 IEEE Annual India Conference (INDICON).

[21]  T. Namerikawa,et al.  A passivity-based approach to wide area stabilization of magnetic suspension systems , 2006, 2006 American Control Conference.

[22]  M. Osman Tokhi,et al.  Fuzzy sliding control with non-linear observer for magnetic levitation systems , 2016, 2016 24th Mediterranean Conference on Control and Automation (MED).

[23]  P. Olver Nonlinear Systems , 2013 .

[24]  Shyam Krishna Nagar,et al.  Optimal fractional order PID controller for magnetic levitation system , 2015, 2015 39th National Systems Conference (NSC).

[25]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[26]  S. L. Shimi,et al.  Modeling, simulation and control of single actuator magnetic levitation system , 2014, 2014 Recent Advances in Engineering and Computational Sciences (RAECS).

[27]  Peter Palensky,et al.  Optimal PID control of Magnetic Levitation System using Genetic Algorithm , 2014, 2014 IEEE International Energy Conference (ENERGYCON).

[28]  Ijlal Haider,et al.  Sliding mode control for electromagnetic levitation system based on feedback linearization , 2015, 2015 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech).

[29]  J. Amarnath,et al.  Rotor levitation by Active Magnetic Bearings using Fuzzy Logic Controller , 2010, 2010 International Conference on Industrial Electronics, Control and Robotics.