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Nonlinear optimal control : = A receding horizon approach.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Nonlinear optimal control :/
其他題名:	A receding horizon approach.
作者:	Primbs, James Alan.
面頁冊數:	1 online resource (130 pages)
附註:	Source: Dissertations Abstracts International, Volume: 61-05, Section: B.
Contained By:	Dissertations Abstracts International61-05B.
標題:	Systems design. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9932855click for full text (PQDT)
ISBN:	9780599333307

Nonlinear optimal control : = A receding horizon approach.
Primbs, James Alan.

Nonlinear optimal control :A receding horizon approach. - 1 online resource (130 pages)

Source: Dissertations Abstracts International, Volume: 61-05, Section: B.

Thesis (Ph.D.)--California Institute of Technology, 1999.

Includes bibliographical references

An exact solution to the nonlinear optimal control problem is known to be prohibitively difficult, both analytically and computationally. Nevertheless, a number of alternative (suboptimal) approaches have been developed. Many of these techniques approach the problem from an off-line, analytical point of view, designing a controller based on a detailed analysis of the system dynamics. A concept particularly amenable to this point of view is that of a control Lyapunov function. These techniques extend the Lyapunov methodology to control systems. In contrast, so-called receding horizon techniques rely purely on on-line computation to determine a control law. While offering an alternative method of attacking the optimal control problem, receding horizon implementations often lack solid theoretical stability guarantees. In this thesis, we uncover a synergistic relationship that holds between control Lyapunov function based schemes and on-line receding horizon style computation. These connections derive from the classical Hamilton-Jacobi-Bellman and Euler-Lagrange approaches to optimal control. By returning to these roots, a broad class of control Lyapunov schemes are shown to admit natural extensions to receding horizon schemes, benefiting from the performance advantages of on-line computation. From the receding horizon point of view, the use of a control Lyapunov function is a convenient solution to not only the theoretical properties that receding horizon control typically lacks, but also unexpectedly eases many of the difficult implementation requirements associated with on-line computation. After developing these schemes for the unconstrained nonlinear optimal control problem, the entire design methodology is illustrated on a simple model of a longitudinal flight control system. They are then extended to time-varying and input constrained nonlinear systems, offering a promising new paradigm for nonlinear optimal control design.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9780599333307Subjects--Topical Terms:

3433840
Systems design.
Subjects--Index Terms:

Lyapunov functionsIndex Terms--Genre/Form:

542853
Electronic books.

Nonlinear optimal control : = A receding horizon approach.
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520 $a An exact solution to the nonlinear optimal control problem is known to be prohibitively difficult, both analytically and computationally. Nevertheless, a number of alternative (suboptimal) approaches have been developed. Many of these techniques approach the problem from an off-line, analytical point of view, designing a controller based on a detailed analysis of the system dynamics. A concept particularly amenable to this point of view is that of a control Lyapunov function. These techniques extend the Lyapunov methodology to control systems. In contrast, so-called receding horizon techniques rely purely on on-line computation to determine a control law. While offering an alternative method of attacking the optimal control problem, receding horizon implementations often lack solid theoretical stability guarantees. In this thesis, we uncover a synergistic relationship that holds between control Lyapunov function based schemes and on-line receding horizon style computation. These connections derive from the classical Hamilton-Jacobi-Bellman and Euler-Lagrange approaches to optimal control. By returning to these roots, a broad class of control Lyapunov schemes are shown to admit natural extensions to receding horizon schemes, benefiting from the performance advantages of on-line computation. From the receding horizon point of view, the use of a control Lyapunov function is a convenient solution to not only the theoretical properties that receding horizon control typically lacks, but also unexpectedly eases many of the difficult implementation requirements associated with on-line computation. After developing these schemes for the unconstrained nonlinear optimal control problem, the entire design methodology is illustrated on a simple model of a longitudinal flight control system. They are then extended to time-varying and input constrained nonlinear systems, offering a promising new paradigm for nonlinear optimal control design.
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