Time-Optimal Control by Iterative Dynamic Programming

Bojkov, Bojan; Luus, Rein

doi:10.1021/ie00030a008

Cited by 33 publications

(36 citation statements)

References 11 publications

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“…Sarkar used the ANNSA approach and obtained a value of 21.789844 . Bojkov et al solved Case 3 by direct search optimization and got a value of 21.744. Balsa‐Canto et al studied the case by using truncated Newton (TN) and a value of 21.8167 was reached , which is, up to now, the best result in the open literature.…”

Section: Resultsmentioning

confidence: 99%

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Control Vector Parameterization‐Based Adaptive Invasive Weed Optimization for Dynamic Processes

et al. 2018

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A novel optimal approach named invasive weed optimization‐control vector parameterization (IWO‐CVP) for chemical dynamic optimization problems is proposed where CVP is used to transform the problem into a nonlinear programming (NLP) problem and an IWO algorithm is then applied to tackle the NLP problem. To improve efficiency, a new adaptive dispersion IWO‐based approach (ADIWO‐CVP) is further suggested to maintain the exploration ability of the algorithm throughout the entire searching procedure. Several classic chemical dynamic optimization problems are tested and detailed comparisons are carried out among ADIWO‐CVP, IWO‐CVP, and other methods. The research results demonstrate that ADIWO‐CVP not only is efficient, but also outperforms IWO‐CVP in terms of both accuracy and convergence speed.

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Section: Resultsmentioning

confidence: 99%

“…The control variables are the flow rates of three feed streams and an electrical energy input used to promote a photochemical reaction. The case has previously been solved to maximize the performance index considering four control variables by several researchers , . An illustration of such a reactor is presented in Fig.…”

Section: Case Studiesmentioning

confidence: 99%

Control Vector Parameterization‐Based Adaptive Invasive Weed Optimization for Dynamic Processes

et al. 2018

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“…Consider the minimum time control of a two-link robotic arm, which has been treated by several authors (Lee, 1992;Bojkov and Luus, 1994;Luus, 2000).…”

Section: Example 3: Two-link Robotic Armmentioning

confidence: 99%

A modified control parametrization method for the numerical solution of bang–bang optimal control problems

Mehrpouya

Fallahi

2013

Journal of Vibration and Control

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In the present paper, an efficient computational method for the solution of bang–bang optimal control problems is investigated. The method is based on control parametrization and belongs to the direct methods for numerical solution of optimal control problems. In this method, control functions are considered to be piecewise constant with values and switching points taken as decision variables. Thereby, the problem is converted into a mathematical programming problem which can be solved by well-developed parameter optimization algorithms. The main advantages of the present method are that: (i) it obtains good results and the switching points can be captured accurately; and (ii) an incorrectly guessed number of switching points can be detected by the results of the method. These are illustrated through three examples and the efficiency of the method is reported.

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“…Essentially, a different optimal control problem is solved completely for each final time candidate before using a Regula Falsi optimization technique to improve upon the estimate of the final time. Their (Bojkov and Luus, 1994b) second approach is a simultaneous solution technique but differs from our proposed approach in three important ways:…”

Section: Introductionmentioning

confidence: 99%

“…The aim, in this article, is to solve efficiently for the optimal control policy and optimal final time simultaneously for time-optimal control problems that exhibit bang-bang or more complicated control policies. The class of problems that can be handled with Bojkov and Luus' (1994b) second method is restricted to those which do not exhibit either boundary control (where state constraints are enforced) or singular control.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Iterative Solution Technique for Time-Optimal Control Using Dynamic Programming

Dadebo¹,

McAuley²

1995

Ind. Eng. Chem. Res.

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Time-Optimal Control by Iterative Dynamic Programming

Cited by 33 publications

References 11 publications

Control Vector Parameterization‐Based Adaptive Invasive Weed Optimization for Dynamic Processes

Control Vector Parameterization‐Based Adaptive Invasive Weed Optimization for Dynamic Processes

A modified control parametrization method for the numerical solution of bang–bang optimal control problems

Simultaneous Iterative Solution Technique for Time-Optimal Control Using Dynamic Programming

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