Parallel asynchronous algorithms for optimal control of large-scale dynamic systems

Abdelwahed, Sherif; Hassan, Mohamed F.; Sultan, M. A.

doi:10.1002/(sici)1099-1514(199707/08)18:4<257::aid-oca600>3.0.co;2-q

Cited by 7 publications

(1 citation statement)

References 7 publications

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“…With a wide variety of applications, many research studies have been focused to investigate efficient parallel computing algorithms to solve OCPs. () In the work of Kunisch et al, a parallel Newton‐Krylov method was employed for the optimal control of monodomain model in cardiac electrophysiology. In the work of Tyatyushkin, a multimethod algorithm in terms of parallel iterative optimization processes was implemented for the OCPs.…”

Section: Introductionmentioning

confidence: 99%

Optimal control of nonlinear dynamical systems based on a new parallel eigenvalue decomposition approach

Jajarmi

Băleanu

2018

Optim Control Appl Methods

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Summary This manuscript aims to investigate a new approach based on the modal series method and eigenvalue decomposition technique to solve a class of nonlinear optimal control problems. For this purpose, a sequence of decoupled linear two‐point boundary value problems is solved iteratively instead of solving the coupled nonlinear two‐point boundary value problem derived from the maximum principle. The convergence analysis of the suggested technique is also investigated. In addition, the problem that needs to be solved at each iteration is composed of lower‐order decoupled subproblems; hence, they can be solved in parallel. Thus, the new scheme has a parallel computing property improving its computational effectiveness. Numerical simulations and comparative results show that the proposed approach is efficient and provides satisfactory results.

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Section: Introductionmentioning

confidence: 99%

Optimal control of nonlinear dynamical systems based on a new parallel eigenvalue decomposition approach

Jajarmi

Băleanu

2018

Optim Control Appl Methods

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Subsystem-level optimal control of weakly coupled linear stochastic systems composed ofN subsystems

Lim

Gajić

1999

Optim. Control Appl. Meth.

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In this paper we introduce a transformation for the exact closed‐loop decomposition of the optimal control and Kalman filtering tasks of linear weakly coupled stochastic systems composed of N subsystems. In addition to having obtained N completely independent reduced‐order subsystem Kalman filters working in parallel, we have obtained the exact solution of the algebraic regulator and filter Riccati equations in terms of the solutions of the corresponding reduced‐order subsystem algebraic Riccati equations. The introduced transformation produces a lot of savings especially for on‐line computations since it allows parallel processing of information with lower‐order‐dimensional Kalman filters. The methodology presented is applied to a 17th‐order cold‐rolling mill. Copyright © 1999 John Wiley & Sons, Ltd.

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Autonomous Transmission Power Adaptation for Multi-Radio Multi-Channel Wireless Mesh Networks

Olwal

Wyk

Djouani

et al. 2009

Ad-Hoc, Mobile and Wireless Networks

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Parallel asynchronous algorithms for optimal control of large-scale dynamic systems

Cited by 7 publications

References 7 publications

Optimal control of nonlinear dynamical systems based on a new parallel eigenvalue decomposition approach

Optimal control of nonlinear dynamical systems based on a new parallel eigenvalue decomposition approach

Subsystem-level optimal control of weakly coupled linear stochastic systems composed ofN subsystems

Autonomous Transmission Power Adaptation for Multi-Radio Multi-Channel Wireless Mesh Networks

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