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Boundary control of parabolic PDE us...

Talaei, Behzad.

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Boundary control of parabolic PDE using adaptive dynamic programming.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Boundary control of parabolic PDE using adaptive dynamic programming./
作者:	Talaei, Behzad.
面頁冊數:	200 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.
Contained By:	Dissertation Abstracts International77-11B(E).
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10133087
ISBN:	9781339915791

Boundary control of parabolic PDE using adaptive dynamic programming.
Talaei, Behzad.

Boundary control of parabolic PDE using adaptive dynamic programming. - 200 p.

Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.

Thesis (Ph.D.)--Missouri University of Science and Technology, 2016.

In this dissertation, novel adaptive/approximate dynamic programming (ADP) based state and output feedback control methods are presented for distributed parameter systems (DPS) which are expressed as uncertain parabolic partial differential equations (PDEs) in one and two dimensional domains. In the first step, the output feedback control design using an early lumping method is introduced after model reduction. Subsequently controllers were developed in four stages; Unlike current approaches in the literature, state and output feedback approaches were designed without utilizing model reduction for uncertain linear, coupled nonlinear and two-dimensional parabolic PDEs, respectively. In all of these techniques, the infinite horizon cost function was considered and controller design was obtained in a forward-in-time and online manner without solving the algebraic Riccati equation (ARE) or using value and policy iterations techniques.

ISBN: 9781339915791Subjects--Topical Terms:

586835
Engineering.

Boundary control of parabolic PDE using adaptive dynamic programming.
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245 1 0 $a Boundary control of parabolic PDE using adaptive dynamic programming.
300 $a 200 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-11(E), Section: B.
500 $a Advisers: Jagannathan Sarangapani; John Singler.
502 $a Thesis (Ph.D.)--Missouri University of Science and Technology, 2016.
520 $a In this dissertation, novel adaptive/approximate dynamic programming (ADP) based state and output feedback control methods are presented for distributed parameter systems (DPS) which are expressed as uncertain parabolic partial differential equations (PDEs) in one and two dimensional domains. In the first step, the output feedback control design using an early lumping method is introduced after model reduction. Subsequently controllers were developed in four stages; Unlike current approaches in the literature, state and output feedback approaches were designed without utilizing model reduction for uncertain linear, coupled nonlinear and two-dimensional parabolic PDEs, respectively. In all of these techniques, the infinite horizon cost function was considered and controller design was obtained in a forward-in-time and online manner without solving the algebraic Riccati equation (ARE) or using value and policy iterations techniques.
520 $a Providing the stability analysis in the original infinite dimensional domain was a major challenge. Using Lyapunov criterion, the ultimate boundedness (UB) result was demonstrated for the regulation of closed-loop system using all the techniques developed herein. Moreover, due to distributed and large scale nature of state space, pure state feedback control design for DPS has proven to be practically obsolete. Therefore, output feedback design using limited point sensors in the domain or at boundaries are introduced. In the final two papers, the developed state feedback ADP control method was extended to regulate multi-dimensional and more complicated nonlinear parabolic PDE dynamics.
590 $a School code: 0587.
650 4 $a Engineering. $3 586835
650 4 $a Mathematics. $3 515831
650 4 $a Applied mathematics. $3 2122814
650 4 $a Systems science. $3 3168411
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710 2 $a Missouri University of Science and Technology. $b Electrical Engineering. $3 2093519
773 0 $t Dissertation Abstracts International $g 77-11B(E).
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