Model-based spatial feedforward for over-actuated motion systems

In high-performance motion systems, e.g. wafer-stages and pick-and-place machines, there is an increasing demand for higher throughput and accuracy. The rigid-body design paradigm aims at very stiff designs, which lead in an evolutionary way to increasingly heavier systems. Such systems require more and more power, such that this paradigm rapidly approaches the boundary of its scalability. An alternative paradigm is to design a lightweight machine with over-actuation and over-sensing, to deal with the resulting flexibilities. This paper presents a spatial feedforward method for over-actuated flexible motions systems, which aims at reducing the vibrations over the complete flexible structure during motion. The proposed method is experimentally validated on an industrial prototype and compared to mass feedforward and the standard input shaping technique.

[1]  William Singhose,et al.  Input shaping/time delay control of maneuvering flexible structures , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[2]  Michel Gevers A decade of progress in iterative process control design: from theory to practice , 2002 .

[3]  P. Sas,et al.  Optimal decoupling for improved multivariable controller design, applied on an automotive vibration test rig , 2003, Proceedings of the 2003 American Control Conference, 2003..

[4]  William Singhose,et al.  Command generation for flexible systems , 1997 .

[5]  Svante Gunnarsson,et al.  Iterative feedback tuning: theory and applications , 1998 .

[6]  T. Singh Optimal Reference Shaping for Dynamical Systems: Theory and Applications , 2009 .

[7]  Hans Butler,et al.  Position Control in Lithographic Equipment [Applications of Control] , 2011, IEEE Control Systems.

[8]  R. Kamidi,et al.  Data-based feed-forward control in MIMO motion systems , 2008, 2008 American Control Conference.

[9]  M. Steinbuch,et al.  Benefits of over-actuation in motion systems , 2004, Proceedings of the 2004 American Control Conference.

[10]  Craig F. Cutforth,et al.  Adaptive input shaping for maneuvering flexible structures , 2004, Autom..

[11]  Hans Butler Adaptive Feedforward for a Wafer Stage in a Lithographic Tool , 2013, IEEE Transactions on Control Systems Technology.

[12]  Tae Tom Oomen,et al.  System identification for robust and inferential control : with applications to ILC and precision motion systems , 2005 .

[13]  M. Steinbuch,et al.  Introduction to an integrated design for motion systems using over-actuation , 2003, 2003 European Control Conference (ECC).

[14]  Kevin L. Moore,et al.  Iterative Learning Control: An Expository Overview , 1999 .

[15]  Okko H. Bosgra,et al.  Hankel Iterative Learning Control for residual vibration suppression with MIMO flexible structure experiments , 2007, 2007 American Control Conference.

[16]  Maarten Steinbuch,et al.  Advanced Motion Control: An Industrial Perspective , 1998, Eur. J. Control.

[17]  Tarunraj Singh,et al.  Minimax Input Shaper Design Using Linear Programming , 2008 .

[18]  Carl D. Meyer,et al.  Matrix Analysis and Applied Linear Algebra , 2000 .

[19]  Jeroen van de Wijdeven,et al.  Using basis functions in iterative learning control: analysis and design theory , 2010, Int. J. Control.

[20]  P. Hughes,et al.  Space structure vibration modes: How many exist? Which ones are important? , 1984, IEEE Control Systems Magazine.

[21]  Adi Ben-Israel,et al.  Generalized inverses: theory and applications , 1974 .

[22]  A. Ruszczynski,et al.  Nonlinear Optimization , 2006 .

[23]  M Maarten Steinbuch,et al.  MODAL FRAMEWORK FOR CLOSED-LOOP ANALYSIS OF OVER-ACTUATED MOTION SYSTEMS , 2004 .

[24]  Maarten Steinbuch,et al.  Feedforward for flexible systems with time-varying performance locations , 2013, 2013 American Control Conference.

[25]  Julián Salt,et al.  Hierarchical Triple-Maglev Dual-Rate Control Over a Profibus-DP Network , 2014, IEEE Transactions on Control Systems Technology.

[26]  M Maarten Steinbuch,et al.  MIMO feed-forward design in wafer scanners using a gradient approximation-based algorithm , 2010 .

[27]  Lucy Y. Pao,et al.  Input shaping and time-optimal control of flexible structures , 2003, Autom..

[28]  J. Spall Multivariate stochastic approximation using a simultaneous perturbation gradient approximation , 1992 .

[29]  Lucy Y. Pao,et al.  Discrete time-optimal command shaping , 2007, Autom..

[30]  Michael T. Heath,et al.  Scientific Computing: An Introductory Survey , 1996 .

[31]  Lucy Y. Pao Multi-input shaping design for vibration reduction , 1999, Autom..

[32]  Manfred Morari,et al.  Interaction measures for systems under decentralized control , 1986, Autom..

[33]  Michel Gevers,et al.  Correlation-based tuning of decoupling multivariable controllers , 2007, Autom..

[34]  H. Butler,et al.  Position control in lithographic equipment , 2013 .

[35]  Håkan Hjalmarsson,et al.  Iterative feedback tuning—an overview , 2002 .

[36]  MF Marcel Heertjes,et al.  Set-point variation in learning schemes with applications to wafer scanners , 2009 .

[37]  Ian Postlethwaite,et al.  Multivariable Feedback Control: Analysis and Design , 1996 .

[38]  Kevin L. Moore,et al.  Iterative Learning Control: Brief Survey and Categorization , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[39]  O. Bosgra,et al.  Residual vibration suppression using Hankel iterative learning control , 2006, 2006 American Control Conference.

[40]  James C. Spall,et al.  A one-measurement form of simultaneous perturbation stochastic approximation , 1997, Autom..

[41]  A.G. Alleyne,et al.  A survey of iterative learning control , 2006, IEEE Control Systems.

[42]  Svante Gunnarsson,et al.  Tuning of a decoupling controller for a 2×2 system using iterative feedback tuning , 2003 .

[43]  Rik Pintelon,et al.  System Identification: A Frequency Domain Approach , 2012 .

[44]  Okko H. Bosgra,et al.  Fixed Structure Feedforward Controller Tuning Exploiting Iterative Trials, Applied to a High-Precision Electromechanical Servo System , 2007, 2007 American Control Conference.

[45]  Max Donath,et al.  American Control Conference , 1993 .

[46]  Tom Oomen,et al.  Inferential motion control: Identification and robust control with unmeasured performance variables , 2011, IEEE Conference on Decision and Control and European Control Conference.

[47]  Panos J. Antsaklis,et al.  Linear Systems , 1997 .

[48]  Marc M. J. van de Wal,et al.  Connecting System Identification and Robust Control for Next-Generation Motion Control of a Wafer Stage , 2014, IEEE Transactions on Control Systems Technology.

[49]  Maarten Steinbuch,et al.  Model-based feedforward for inferential motion systems, with application to a prototype lightweight motion system , 2012, 2012 American Control Conference (ACC).

[50]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[51]  Qingze Zou,et al.  A review of feedforward control approaches in nanopositioning for high-speed spm , 2009 .

[52]  M Maarten Steinbuch,et al.  Trajectory planning and feedforward design for electromechanical motion systems , 2005 .

[53]  Okko Bosgra,et al.  Fixed Structure Feedforward Controller Design Exploiting Iterative Trials: Application to a Wafer Stage and a Desktop Printer , 2008 .

[54]  Niels van Dijk,et al.  Combined input shaping and feedforward control for flexible motion systems , 2012, 2012 American Control Conference (ACC).

[55]  Richard W. Longman,et al.  Iterative learning control and repetitive control for engineering practice , 2000 .

[56]  M Maarten Steinbuch,et al.  Advanced Motion Control Design , 2010 .