The numerical solution of differential equations arising in control theory for lumped and distributed parameter systems

Author(s):  
L. Graney
2021 ◽  
Vol 20 ◽  
pp. 66-78
Author(s):  
Raheam Al-Saphory ◽  
Ahlam Y Al-Shaya

This paper is aimed at investigating and introducing the main results regarding the concept of Regional Boundary Gradient Strategic Sensors (RBGS-sensors  the in Diffusion Distributed Parameter Systems (DDP-Systems  . Hence, such a method is characterized by Parabolic Differential Equations (PDEs  in which the behavior of the dynamic is created by a Semigroup ( of Strongly Continuous type (SCSG  in a Hilbert Space (HS) . Additionally , the grantee conditions which ensure the description for such sensors are given respectively to together with the Regional Boundary Gradient Observability (RBG-Observability  can be studied and achieved . Finally , the results gotten are applied to different situations with altered sensors positions are undertaken and examined.


Author(s):  
Jianping Zhou ◽  
Zhigang Feng

Abstract A semi-analytic method is presented for the analysis of transient response of distributed parameter systems which are consist of one dimensional subsystems. The system is first divided into one dimensional sub-systems. Within each subsystem, replacing differentials on time t by finite difference, the governing partial differential equations are reduced to difference-differential equations. The solution of derived ordinary differential equations is obtained in an exact and closed form by distributed transfer function method and represented in nodal displacement parameters. Assemling global equilibrium equations at each nodes according to displacement continuity and force equilibrium requirements gives simutaneous linear algebraic equations. Numerical results are illustrated and compared with that of finite element method.


1969 ◽  
Vol 91 (2) ◽  
pp. 190-194 ◽  
Author(s):  
D. A. Wismer

The optimal control problem for a broad class of distributed parameter systems defined by vector parabolic partial differential equations is considered. The problem is solved by discretizing the spatial domain and then treating the (large) resultant set of ordinary differential equations as a set of independent subsystems. The subsystems are determined by decomposition of the total system into lower-dimensional problems and the necessary conditions for optimality of the overall system are then satisfied by an iterative procedure. With this treatment, the optimal control problem can be solved for larger systems (or finer spatial discretizations) than would otherwise be feasible. An example is given for a system described by a nonlinear parabolic partial differential equation in one space dimension.


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