scholarly journals Discussion: “A Design Procedure for a Class of Distributed Parameter Control Systems” (Orner, P. A., and Foster, A. M., 1971, ASME J. Dyn. Syst., Meas., Control, 93, pp. 86–92)

1971 ◽  
Vol 93 (2) ◽  
pp. 92-93 ◽  
Author(s):  
R. E. Klein
Keyword(s):  
Control Systems ◽  
Design Procedure ◽  
Distributed Parameter ◽  
Parameter Control ◽  
Distributed Parameter Control

scholarly journals A New Type of Distributed Parameter Control Systems: Two-Point Boundary Value Problems for Infinite-Dimensional Dynamical Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-3
Author(s):  
De-Xing Kong ◽  
Fa Wu
Keyword(s):  
Dynamical Systems ◽  
Boundary Value Problems ◽  
Control Systems ◽  
Distributed Parameter ◽  
Parameter Control ◽  
Point Boundary ◽  
Infinite Dimensional ◽  
Infinite Dimensional Dynamical Systems ◽  
Distributed Parameter Control ◽  
New Type

This survey note describes a new type of distributed parameter control systems—the two-point boundary value problems for infinite-dimensional dynamical systems, particularly, for hyperbolic systems of partial differential equations of second order, some of the discoveries that have been done about it and some unresolved questions.

A Design Procedure for a Class of Distributed Parameter Control Systems

1971 ◽  
Vol 93 (2) ◽  
pp. 86-92 ◽  
Author(s):  
P. A. Orner ◽  
A. M. Foster
Keyword(s):  
Control Systems ◽  
Design Procedure ◽  
Optimal Location ◽  
Galerkin Projection ◽  
Distributed Parameter ◽  
Dimensional Model ◽  
Plant Model ◽  
Finite Dimensional ◽  
Distributed Parameter Control ◽  
Linear Scalar

A rational deterministic design procedure is presented for a class of distributed parameter multivariable plants described by linear scalar differential equations. The Galerkin projection method is employed to form an approximate finite dimensional plant model. The subsequent solution of a quadratic regulator problem for the finite dimensional model results in a lumped multivariable controller which operates on the inputs and outputs of the actual plant. A deterministic observer is constructed to estimate the model state. Techniques for optimal location of the input zones and output transducers are developed. Two examples are presented.

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