Performance Limitations and Self-Sensing Magnetic Bearings

Magnetic bearings levitate a rotating object (typically, a rotor) with a magnetic field, and are unstable in open-loop operation. Position feedback control is required to maintain the rotor in a centered position. Typically, a separate position sensor is used to directly measure the rotor’s position for use in this feedback loop. Self-sensing magnetic bearings use the bearing’s electrical signals to estimate rotor position. There are two primary classes of self-sensing methods: state estimation and ripple-based. State estimation approaches model the bearing as a linear, time-invariant system and treat the rotor position as a state to be estimated as part of linear, time-invariant feedback control. Ripple-based approaches rely on effects of the driving switching amplifier to estimate position. The self-sensing method presented here is a ripple-based approach, in that it generates estimates of position from switching voltage and current signals. The primary impediment to many schemes is achieving acceptable robustness to plant parameter variations. System theory for linear, time invariant plants provides explicit measures of achievable robustness, but there are no such analyses for ripple-based approaches. While many researchers discuss such problems, none has provided quantified measures of such robustness. Many researchers of ripple-based approaches claim that their techniques achieve higher stability robustness than the state estimation approaches, but none has provided theoretical or experimental measures that attempt to quantify such robustness improvement. Furthermore, for ripple-based approaches, there is no design and analysis method to replace the current ad-hoc methods of ripple-based design and implementation. Simulation and experimental data demonstrate that the self-sensing method presented here can make a viable active magnetic bearing system. Gain margin comparisons demonstrate that our ripple-based approach appears to have higher robustness than what would be expected from a corresponding ripple-less self-sensing scheme. Furthermore, robustness measures calculated for a linear, periodic model of the bearing suggest that the ripple is the mechanism which provides added robustness to self-sensing systems.

[1]  J. Freudenberg,et al.  Right half plane poles and zeros and design tradeoffs in feedback systems , 1985 .

[2]  J. Edmunds,et al.  Principal gains and principal phases in the analysis of linear multivariable feedback systems , 1981 .

[3]  Myounggyu Noh,et al.  Self{Sensing Magnetic Bearings Driven by a Switching Power Amplier , 1996 .

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

[5]  Seth R. Sanders,et al.  A self-sensing homopolar magnetic bearing: analysis and experimental results , 1999, Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370).

[6]  Henry D'Angelo,et al.  Linear time-varying systems : analysis and synthesis , 1970 .

[7]  E. H. Maslen,et al.  Position estimation in magnetic bearings using inductance measurements , 1995 .

[8]  Pablo A. Iglesias,et al.  Tradeoffs in linear time-varying systems: an analogue of Bode's sensitivity integral , 2001, Autom..

[9]  G. Stein,et al.  Multivariable feedback design: Concepts for a classical/modern synthesis , 1981 .

[10]  Mochimitsu Komori,et al.  Superconducting Bearings Assisted by Self-sensing AMBs in Liquid Nitrogen ( Magnetic Bearing) , 2003 .

[11]  Virendra R. Sule,et al.  Steady-state frequency response for periodic systems , 2001, J. Frankl. Inst..

[12]  J. Schumacher,et al.  A nine-fold canonical decomposition for linear systems , 1984 .

[13]  Geir E. Dullerud,et al.  A new approach for analysis and synthesis of time-varying systems , 1999, IEEE Trans. Autom. Control..

[14]  G. Zames,et al.  Feedback, minimax sensitivity, and optimal robustness , 1983 .

[15]  Richard Markert,et al.  Compensation of disturbances on self-sensing magnetic bearings caused by saturation and coordinate coupling , 2000 .

[16]  Fumio Harashima,et al.  Industrial application of position sensorless active magnetic bearings , 1996 .

[17]  Antonio Tornambè,et al.  On the analysis of periodic linear systems , 1996, Kybernetika.

[18]  G. Zames,et al.  On H ∞ -optimal sensitivity theory for SISO feedback systems , 1984 .

[19]  James F. Antaki,et al.  Position sensed and self-sensing magnetic bearing configurations and associated robustness limitations , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[20]  N. Karcanias,et al.  Poles and zeros of linear multivariable systems : a survey of the algebraic, geometric and complex-variable theory , 1976 .

[21]  S. Lee,et al.  On linear periodic controllers , 1987, 26th IEEE Conference on Decision and Control.

[22]  K. K. Sivadasan,et al.  Analysis of self-sensing active magnetic bearings working on inductance measurement principle , 1996 .

[23]  B. B. Pati,et al.  An investigation of forced oscillation for signal stabilisation of two-dimensional nonlinear system , 1998 .

[24]  J. Bay Fundamentals of Linear State Space Systems , 1998 .

[25]  J. Cruz,et al.  A new approach to the sensitivity problem in multivariable feedback system design , 1964 .

[26]  Olli Aumala Turning interference and noise into improved resolution , 1996 .

[27]  T. Mizuno,et al.  Self-sensing magnetic suspension using hysteresis amplifiers , 1996 .

[28]  Eric H. Maslen,et al.  Experimental Self-Sensing Results for a Magnetic Bearing , 2001 .

[29]  Richard H. Middleton,et al.  An integral constraint for single input two output feedback systems , 2001, Autom..

[30]  Graham C. Goodwin,et al.  Sensitivity limitations in nonlinear feedback control , 1996 .

[31]  José Carlos Goulart de Siqueira,et al.  Differential Equations , 1919, Nature.

[32]  V.M.G. van Acht On self-sensing magnetic levitated systems , 1998 .

[33]  Ladislav Kucera,et al.  Robustness of Self-Sensing Magnetic Bearing , 1997 .

[34]  David J. N. Limebeer,et al.  Linear Robust Control , 1994 .

[35]  Giuseppe De Nicolao,et al.  Zeros of Continuous-time Linear Periodic Systems , 1998, Autom..

[36]  H. W. Bode,et al.  Network analysis and feedback amplifier design , 1945 .

[37]  T. Başar Feedback and Optimal Sensitivity: Model Reference Transformations, Multiplicative Seminorms, and Approximate Inverses , 2001 .

[38]  Kenji Araki,et al.  Counter-Interfaced Digital Control of Self-Sensing Magnetic Suspension Systems with Hysteresis Amplifiers , 1999 .

[39]  K. Poolla,et al.  Robust control of linear time-invariant plants using periodic compensation , 1985 .

[40]  Norman M. Wereley,et al.  Frequency response of linear time periodic systems , 1990, 29th IEEE Conference on Decision and Control.

[41]  Rick H. Middleton,et al.  Trade-offs in linear control system design , 1991, Autom..

[42]  Joos Vandewalle,et al.  Trade-offs in linear control system design: a practical example , 1992 .

[43]  Richard Markert,et al.  Improvements in the integration of active magnetic bearings , 2000 .

[44]  Myounggyu Noh,et al.  Self-sensing magnetic bearings using parameter estimation , 1997 .

[45]  T. Runolfsson,et al.  Vibrational feedback control: Zeros placement capabilities , 1987 .

[46]  Robin J. Evans,et al.  Minimization of the Bode sensitivity integral , 2000 .

[47]  Geir E. Dullerud,et al.  Computing quasi-LTI robustness margins in sampled-data systems , 2001, IEEE Trans. Autom. Control..

[48]  A. Laub,et al.  Feedback properties of multivariable systems: The role and use of the return difference matrix , 1981 .

[49]  Roy M. Howard,et al.  Linear System Theory , 1992 .

[50]  Glyn James,et al.  Operational Methods for Linear Systems , 1963 .

[51]  T. Runolfsson,et al.  Linear periodic feedback: Zeros placement capabilities , 1986, 1986 25th IEEE Conference on Decision and Control.

[52]  B. Moore Principal component analysis in linear systems: Controllability, observability, and model reduction , 1981 .

[53]  D. Vischer,et al.  A New Approach to Sensor-less and Voltage Controlled AMBs Based on Network Theory Concepts , 1990 .

[54]  Richard Markert,et al.  Influence of cross-axis sensitivity and coordinate coupling on self-sensing , 2001 .

[55]  Fumio Harashima,et al.  An Industrial Application of Position Sensorless Active Magnetic Bearings , 1996 .

[56]  N. DeClaris,et al.  Asymptotic methods in the theory of non-linear oscillations , 1963 .

[57]  M. Sain Finite dimensional linear systems , 1972 .

[58]  Pramod P. Khargonekar,et al.  Frequency response of sampled-data systems , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[59]  Olli Aumala,et al.  Dithering design for measurement of slowly varying signals , 1998 .

[60]  G. Dullerud,et al.  A Course in Robust Control Theory: A Convex Approach , 2005 .

[61]  V. Cheng,et al.  Limitations on the closed-loop transfer function due to right-half plane transmission zeros of the plant , 1980 .

[62]  Yohji Okada,et al.  Self-Sensing Control Technique of Self-Bearing Motor , 2004 .

[63]  Charles A. Desoer,et al.  Zeros and poles of matrix transfer functions and their dynamical interpretation , 1974 .

[64]  Michael Green,et al.  Workshop on H ∞ and μ methods for robust control , 1991 .

[65]  Abdelfatah M. Mohamed,et al.  Modeling and robust control of self-sensing magnetic bearings with unbalance compensation , 1997, Proceedings of the 1997 IEEE International Conference on Control Applications.