Advanced Attitude and Position MIMO Robust Control Strategies for Telescope-Type Spacecraft with Large Flexible Appendages

With extraordinary high priority science objectives to break the current barriers of our knowledge of the universe, and dealing with significant weight limitations of launch vehicle for cost-effective access to space, several NASA and ESA missions will involve both formation flying technology and satellites with large flexible structures in the next few decades: Terrestrial Planet Finder, Stellar and Planet Imager, Life Finder, Darwin and Lisa missions, etc. This chapter deals with the design of multi-input multi-output (MIMO) robust control strategies to regulate simultaneously the position and attitude of a telescope-type spacecraft with large flexible appendages. Section 2 describes the main control challenges and dynamic characteristics of a MIMO system in general, and a spacecraft in particular; Section 3 presents advanced techniques to design MIMO robust controllers based on the quantitative feedback theory (QFT); and Section 4 shows some illustrative results achieved when applying the MIMO QFT control methodology to one of the telescope-type spacecraft (a 6inputs/6-outputs MIMO system) of a multiple formation flying constellation of a European Space Agency (ESA) cornerstone mission (Fig. 1). Control of spacecraft with large flexible structures and very demanding astronomical performance specifications, as the telescope-type satellite mission, involves significant difficulties due to the combination of a large number of flexible modes with small damping, model uncertainty and coupling among the inputs and outputs. The scientific objectives of such missions require very demanding control specifications, as micrometer accuracy for position and milli-arc-second precision for attitude, high disturbance rejection properties, loop-coupling attenuation and low controller complexity and order. The dynamics of such spacecraft usually present a complex 6-inputs/6-outputs MIMO plant, with 36 transfer functions with high order dynamics (50th order models in our example), large model uncertainty and high loop interactions introduced by the flexible modes of the low-stiffness appendages. This chapter presents advanced tools and techniques to analyse and design MIMO robust control systems to regulate simultaneously the position and attitude of telescope-type spacecraft with large flexible appendages.

[1]  P. J. Campo,et al.  Achievable closed-loop properties of systems under decentralized control: conditions involving the steady-state gain , 1994, IEEE Trans. Autom. Control..

[2]  Cheng-Ching Yu,et al.  Relative disturbance gain array , 1992 .

[3]  Thomas J. McAvoy,et al.  Interaction analysis : principles and applications , 1983 .

[4]  Thomas Kailath,et al.  Linear Systems , 1980 .

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

[6]  Suhada Jayasuriya,et al.  On stability in nonsequential MIMO QFT designs , 2005 .

[7]  Isaac Horowitz,et al.  Design of a 3×3 multivariable feedback system with large plant uncertainty† , 1981 .

[8]  H. Rosenbrock Design of multivariable control systems using the inverse Nyquist array , 1969 .

[9]  Edward Boje,et al.  Quantitative multivariable feedback design for a turbofan engine with forward path decoupling , 1999 .

[10]  W. Wolovich State-space and multivariable theory , 1972 .

[11]  C. Desoer,et al.  Feedback Systems: Input-Output Properties , 1975 .

[12]  M. Barreras Multivariable QFT Controllers Design for Heat Exchangers of Solar Systems , 2004 .

[13]  N. Karcanias,et al.  Relationships Between State-Space and Frequency-Response Concepts , 1978 .

[14]  Maciejowsk Multivariable Feedback Design , 1989 .

[15]  S. Jayasuriya,et al.  Sufficient conditions for robust stability in non-sequential MIMO QFT , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[16]  Samir Bennani,et al.  Non‐diagonal MIMO QFT controller design reformulation , 2009 .

[17]  Matthew A. Franchek,et al.  Robust multivariable control of distillation columns using a non-diagonal controller matrix , 1995 .

[18]  Richard R. Sating Development of an Analog MIMO Quantitative Feedback Theory (QFT) CAD Package , 1992 .

[19]  J. Doyle Robustness of multiloop linear feedback systems , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

[20]  W. Wolovich Linear multivariable systems , 1974 .

[21]  Mario Garcia-Sanz,et al.  Quantitative non‐diagonal controller design for multivariable systems with uncertainty , 2002 .

[22]  Christopher I. Byrnes A complex variable approach to the analysis of linear multivariable feedback systems [Book reviews] , 1981, IEEE Transactions on Automatic Control.

[23]  Marcel J. Sidi,et al.  Design of Robust Control Systems: From Classical to Modern Practical Approaches , 2001 .

[24]  Edward Boje,et al.  Quantitative Feedback Design Using Forward Path Decoupling , 2001 .

[25]  Mario Garcia-Sanz,et al.  Nondiagonal QFT Controller Design for a Three-Input Three-Output Industrial Furnace , 2006 .

[26]  O. D. I. Nwokah,et al.  Synthesis of controllers for uncertain multivariable plants for prescribed time-domain tolerances† , 1984 .

[27]  A. Mees Achieving diagonal dominance , 1981 .

[28]  B. McMillan Introduction to formal realizability theory — II , 1952 .

[29]  E. Davison,et al.  Properties and calculation of transmission zeros of linear multivariable systems , 1974, Autom..

[30]  Isaac Horowitz,et al.  Multivariable Flight Control Design with Uncertain Parameters. , 1982 .

[31]  M. Morari,et al.  Effect of disturbance directions on closed-loop performance , 1987 .

[32]  Samir Bennani,et al.  Nondiagonal MIMO QFT Controller Design for Darwin-Type Spacecraft With Large Flimsy Appendages , 2008 .

[33]  Fred Y. Hadaegh,et al.  Load-sharing robust control of spacecraft formations: deep space and low Earth elliptic orbits , 2007 .

[34]  David Q. Mayne,et al.  The Design of Linear Multivariable Systems , 1972 .

[35]  Mario Garcia-Sanz,et al.  NON-DIAGONAL MULTIVARIABLE ROBUST QFT CONTROL OF A WASTEWATER TREATMENT PLANT FOR SIMULTANEOUS NITROGEN AND PHOSPHORUS REMOVAL , 2006 .

[36]  C. Desoer,et al.  On the generalized Nyquist stability criterion , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[37]  Murray Lawrence Kerr Robust control of an articulating flexible structure using MIMO QFT , 2004 .

[38]  M. Morari,et al.  Implications of large RGA elements on control performance , 1987 .

[39]  H. Rosenbrock The zeros of a system , 1973 .

[40]  Isaac Horowitz,et al.  Quantitative feedback design theory : QFT , 1993 .

[41]  I. Horowitz Survey of quantitative feedback theory (QFT) , 2001 .

[42]  Evanghelos Zafiriou,et al.  Robust process control , 1987 .

[43]  Oded Yaniv,et al.  An important property of non-minimum-phase multiple-input-multiple-output feedback systems , 1986 .

[44]  Constantine H. Houpis,et al.  MIMO QFT CAD PACKAGE (VERSION 3) , 1997 .

[45]  Suhada Jayasuriya,et al.  Non‐sequential MIMO QFT control of the X‐29 aircraft using a generalized formulation , 2007 .

[46]  Matthew A. Franchek,et al.  Robust Nondiagonal Controller Design for Uncertain Multivariable Regulating Systems , 1997 .

[47]  J. Freudenberg,et al.  Frequency Domain Properties of Scalar and Multivariable Feedback Systems , 1988 .

[48]  Mario Garcia Sanz Design of quantitative feedback theory non-diagonal controllers for use in uncertain multiple-input multiple-output systems , 2005 .

[49]  L. Kantorovich,et al.  Functional analysis in normed spaces , 1952 .

[50]  Manfred Morari,et al.  A computer aided methodology for the design of decentralized controllers , 1987 .

[51]  M. Morari,et al.  Closed-loop properties from steady-state gain information , 1985 .

[52]  H. H. Rosenbrock,et al.  Computer Aided Control System Design , 1974, IEEE Transactions on Systems, Man, and Cybernetics.

[53]  J. M. De Bedout,et al.  Stability conditions for the sequential design of non-diagonal multivariable feedback controllers , 2002 .

[54]  Sigurd Skogestad,et al.  Simple frequency-dependent tools for control system analysis, structure selection and design , 1992, Autom..

[55]  M Maarten Steinbuch,et al.  A new approach to multivariable quantitative feedback theory: theoretical and experimental results , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[56]  Oded Yaniv MIMO QFT using non-diagonal controllers , 1995 .

[57]  I. Postlethwaite,et al.  The generalized Nyquist stability criterion and multivariable root loci , 1977 .

[58]  Isaac Horowitz,et al.  The singular-G method for unstable non-minimum-phase plants , 1986 .

[59]  G. Stein,et al.  Performance and robustness analysis for structured uncertainty , 1982, 1982 21st IEEE Conference on Decision and Control.

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

[61]  O. Nwokah The design of linear multivariable systems , 1975 .

[62]  Sigurd Skogestad,et al.  The use of RGA and condition number as robustness measures , 1996 .

[63]  Isaac Horowitz,et al.  Practical design of feedback systems with uncertain multivariable plants , 1980 .

[64]  Isaac Horowitz Improved design technique for uncertain multiple-input-multiple-output feedback systems† , 1982 .

[65]  T. J. McAvoy,et al.  Using the Relative Disturbance Gain to Analyse Process Operability , 1985, 1985 American Control Conference.

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

[67]  I. Horowitz Quantitative synthesis of uncertain multiple input-output feedback system† , 1979 .

[68]  Ian Postlethwaite,et al.  A Complex Variable Approach to the Analysis of Linear Multivariable Feed Back Systems , 1979 .

[69]  Marta Barreras Carracedo Control robusto QFT multivariable mediante métodos secuenciales no-diagonales. Aplicación al gobierno de procesos térmicos , 2005 .

[70]  Suhada Jayasuriya,et al.  An improved non‐sequential multi‐input multi‐output quantitative feedback theory design methodology , 2006 .

[71]  I. Horowitz,et al.  A quantitative design method for MIMO linear feedback systems having uncertain plants , 1985, 1985 24th IEEE Conference on Decision and Control.

[72]  Constantine H. Houpis,et al.  Linear Control System Analysis and Design with MATLAB , 2013 .

[73]  Pradeep B. Deshpande Multivariable process control , 1989 .

[74]  John C. Doyle Analysis of Feedback Systems with Structured Uncertainty , 1982 .

[75]  Ken Dutton,et al.  The art of control engineering , 1988 .

[76]  J. Kalkkuhl,et al.  Robust QFT tracking controller design for a car equipped with 4-wheel steer-by-wire , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

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

[78]  Steven J. Rasmussen,et al.  Quantitative feedback theory: fundamentals and applications: C. H. Houpis and S. J. Rasmussen; Marcel Dekker, New York, 1999, ISBN: 0-8247-7872-3 , 2001, Autom..

[79]  M. Fan,et al.  Decentralized integral controllability and D-stability , 1990 .

[80]  Heinz A. Preisig,et al.  A new criterion for the pairing of control and manipulated variables , 1986 .

[81]  Ching-Hwang Hsu,et al.  A proof of the stability of multivariable feedback systems , 1968 .

[82]  Uri Shaked,et al.  Synthesis of multivariable, basically non-interacting systems with significant plant uncertainty , 1976, Autom..

[83]  Osita D. I. Nwokah,et al.  Strong robustness in uncertain multivariable systems , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[84]  B. de Jager,et al.  Control structure design: a survey , 1995 .

[85]  S. Jayasuriya,et al.  Synthesis of controllers for non-minimum phase and unstable systems using non-sequential MIMO quantitative feedback theory , 2004, Proceedings of the 2004 American Control Conference.

[86]  David Q. Mayne The design of linear multivariable systems , 1973 .

[87]  A. J. Macfarlane,et al.  Use of parameter groups in the analysis and design of multivariable feedback systems , 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[88]  Isaac Horowitz,et al.  Limitations of non-minimum-phase feedback systems† , 1984 .

[89]  E. Bristol On a new measure of interaction for multivariable process control , 1966 .

[90]  Min-Sen Chiu,et al.  Decentralized control structure selection based on integrity considerations , 1990 .

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

[92]  Jacob Katzenelson,et al.  A generalized Nyquist-type stability criterion for multivariable feedback systems† , 1974 .

[93]  I. Postlethwaite A generalized inverse Nyquist stability criterion , 1977 .

[94]  I. Horowitz Synthesis of feedback systems , 1963 .

[95]  Vasilios Manousiouthakis,et al.  Synthesis of decentralized process control structures using the concept of block relative gain , 1986 .

[96]  D. Q. Mayne Sequential design of linear multivariable systems , 1979 .

[97]  H. Rosenbrock Correspondence : Correction to ‘The zeros of a system’ , 1974 .