Controller design for partial decoupling of linear multivariable systems

In the design of feedback control systems for linear multivariable plants, insisting on the elimination of coupling in closed-loop is often achieved at the expense of an increase in the multiplicity of infinite and non-minimum phase zeros beyond those of the plant plant. This behaviour is known as the ‘cost of decoupling’ since these additional zeros are manifested in the time domain by increased rise times and undershoots in step responses. Using partially decoupling controllers, however, it is always possible to obtain closed-loop systems with precisely the same number of infinite and non-minimum phase zeros as the plant, albeit at the expense of a restricted form of transient coupling. This paper uses a generalization of the interactor matrix to generate a class of partially decoupling controllers for square, stable plants in which diagonal decoupling arises as a special case, thereby permitting the designer to trade off speed of response versus the severity of transient interaction.

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

[2]  Dante C. Youla,et al.  Modern Wiener-Hopf Design of Optimal Controllers. Part I , 1976 .

[3]  A. Vardulakis Linear Multivariable Control: Algebraic Analysis and Synthesis Methods , 1991 .

[4]  Sigurd Skogestad,et al.  Robust control of ill-conditioned plants: high-purity distillation , 1988 .

[5]  Nicos Karcanias,et al.  On the stable exact model matching problem , 1985 .

[6]  C. Desoer,et al.  Feedback system design: The fractional representation approach to analysis and synthesis , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[7]  L. Pernebo An algebraic theory for design of controllers for linear multivariable systems--Part II: Feedback realizations and feedback design , 1981 .

[8]  K. Furuta,et al.  State feedback and inverse system , 1977 .

[9]  P. Falb,et al.  Invariants and Canonical Forms under Dynamic Compensation , 1976 .

[10]  Manfred Morari,et al.  Digital controller design for multivariable systems with structural closed-loop performance specifications , 1987 .

[11]  Graham C. Goodwin,et al.  The role of the interactor matrix in multivariable stochastic adaptive control , 1984, Autom..

[12]  C. Desoer,et al.  Multivariable Feedback Systems , 1982 .

[13]  G. Zames Feedback and optimal sensitivity: Model reference transformations, multiplicative seminorms, and approximate inverses , 1981 .

[14]  Brian D. O. Anderson,et al.  Triangularization technique for the design of multivariable control systems , 1978 .

[15]  George Stephanopoulos,et al.  Chemical Process Control: An Introduction to Theory and Practice , 1983 .

[16]  Christos A. Tsiligiannis,et al.  Dynamic interactors in multivariable process control—I. The general time delay case , 1988 .

[17]  C. Desoer,et al.  Decoupling linear multiinput multioutput plants by dynamic output feedback: An algebraic theory , 1986 .

[18]  Graham C. Goodwin,et al.  Digital control and estimation : a unified approach , 1990 .

[19]  L. Pernebo An algebraic theory for design of controllers for linear multivariable systems--Part I: Structure matrices and feedforward design , 1981 .

[20]  W. Wolovich,et al.  A parameter adaptive control structure for linear multivariable systems , 1982 .

[21]  Christos A. Tsiligiannis,et al.  Dynamic interactors in multivariable process control—II. Time delays and zeroes outside the unit circle , 1989 .