Method of modelling linear time-invariant distributed-parameter systems by pseudorandom binary sequences

1976 ◽  
Vol 12 (1) ◽  
pp. 29 ◽  
Author(s):  
C.J. Macleod ◽  
D.R. Campbell
1992 ◽  
Vol 114 (3) ◽  
pp. 339-346 ◽  
Author(s):  
A. J. Helmicki ◽  
C. A. Jacobson ◽  
C. N. Nett

In this paper the use of linear, time-invariant, distributed parameter systems (LTI-DPS) as models of physical processes is considered from a control viewpoint. Specifically, recent theoretical results obtained by the authors for the control-oriented modeling of LTI-DPS are concisely reviewed and then a series of applications is given in order to illustrate the practical ramifications of these results.


2012 ◽  
Vol 482-484 ◽  
pp. 1809-1815
Author(s):  
Gui Ge Gao ◽  
Xian Wen Zeng

The distributed parameter systems(DPS) are usually described by the partial differential equations(PDEs). Compared the variable structure control problem of DPS with that of the lumped parameter systems(LPS) , it is more complicated because the problem of variable structure control for DPS is often closely related to the theory of the differential operator or integral operator. Based on Haar wavelets transform, the operational matrixes and their characteristics, this paper attempts to propose a new approach for the variable structure control problem of a class linear time-invariant DPS by converting it into that of lumped parameter systems(LPS) and then makes use of the mature research methods of LPS to design the variable structure control problem so as to solve the variable structure control problem of DPS. The proposed method in this paper has the advantages of the simpler algorithm, less computation and better control effect. The simulation results also prove that it is an efficient algorithm for DPS.


1988 ◽  
Vol 110 (4) ◽  
pp. 436-440 ◽  
Author(s):  
B. M. Mohan ◽  
K. B. Datta

In this paper, one shot operational matrix for repeated integration of the shifted Legendre polynomial basis vector is developed and double-shifted Legendre series is introduced to approximate functions of two independent variables. Then using these, systematic algorithms for the identification of linear time-invariant single input-single output continuous lumped and distributed parameter systems are presented. Illustrative examples are provided with satisfactory results.


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