• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.671-680
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• 2007

The objective of this work is to reduce drag on a bluff body within a viscous flow by applying suction or injection of fluid along the surface of the body. In addition to minimizing drag, the optimal solution tends to reduce boundary layer separation and flow recirculation. When discretized by finite elements, the optimal control problem can be posed as a large-scale nonlinearly-constrained optimization problem. The constraints correspond to the discretized form of the Navier-Stokes equations. Unfortunately, solving such large-scale problems directly is essentially intractable. We developed several Sequential Quadratic Programming methods that are tailored to the structure of the control problem. Example problems of laminar flow around an infinite cylinder in two dimensions are solved to demonstrate the methodology. We use these optimal control techniques to study the influence of number of suction/injection holes and location of holes on the resulting optimized flow. We compare the proposed SQP methods against one another, as well as against available methods from the literature, from the point of view of efficiency and robustness. The most efficient of the proposed methods is two orders of magnitude faster than existing methods.

• East Asian mathematical journal
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• v.17 no.2
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• pp.375-383
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• 2001

In this paper we deal with the duality theory of optimality for an optimal control problem governed by a class of second order evolution equations. First we establish the dual control systems by using conjugate functions and then associate them to the original optimization problem.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.717-730
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• 2002

In this paper we use measure theory to solve a wide range of the nonlinear programming problems. First, we transform a nonlinear programming problem to a classical optimal control problem with no restriction on states and controls. The new problem is modified into one consisting of the minimization of a special linear functional over a set of Radon measures; then we obtain an optimal measure corresponding to functional problem which is then approximated by a finite combination of atomic measures and the problem converted approximately to a finite-dimensional linear programming. Then by the solution of the linear programming problem we obtain the approximate optimal control and then, by the solution of the latter problem we obtain an approximate solution for the original problem. Furthermore, we obtain the path from the initial point to the admissible solution.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1065-1070
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• 2004

Optimal collision avoidance algorithm for unmanned aerial vehicles based on proportional navigation guidance law is investigated this paper. Although proportional navigation guidance law is widely used in missile guidance problems, it can be used in collision avoidance problem by guiding the relative velocity vector to collision avoidance vector. The optimal navigation coefficient can be obtained if an obstacle if an obstacle moves at constant velocity vector. The stability of the proposed algorithm is also investigated. The stability can be obtained by choosing a proper navigation coefficient.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.578-583
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• 1992

In this paper, we show that various navigation constant values in PNG law can result in as optimal gains when we introduce proper time-varying weighting functions into the cost function of an optimal control problem. we then apply this idea to the guidance problem where we are required to achieve a given impact angle as well as the zero miss distance. As a result, we obtain a set of optimal guidance laws each of which could be related to a navigation constant in PNG. Some basic properties of these guidance laws are also presented.

• Journal of applied mathematics & informatics
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• v.32 no.5_6
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• pp.707-719
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• 2014

In this paper, we investigate a variational discretization approximation of elliptic optimal control problems with control constraints. The state and the co-state are approximated by piecewise linear functions, while the control is not directly discretized. By using some proper intermediate variables, we derive a second-order convergence in $L^2$-norm and superconvergence between the numerical solution and elliptic projection of the exact solution in $H^1$-norm or the gradient of the exact solution and recovery gradient in $L^2$-norm. Then we construct a posteriori error estimates by using the superconvergence results and do some numerical experiments to confirm our theoretical results.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.234-239
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• 1993

Most of the control problem is for the redundant manipulators use the pseudo-inverse control, thit is, the redundancy is resolved by the pseudo-inverse of the Jacobian matrix and then the controller is designed based on this resolution. However, this pseudo-inverse control has some problems when the redundant robot repeats the cyclic tasks. This is because the pseudo-inverse resolution is a local solution that generates the different configurations of the robot arm for the same hand position. Therefore it is necessary to find the global solution that maintains the optimal configuration of the robot for the repetitive tasks. In this paper, we want to propose a redundancy resolution method by the optimal theory that uses the calculus of variation. The problem formulations are : first to convert the optimal resolution problem to an optimal control problem and then to resolve the redundancy using the necessary conditions of optimal control.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.359-365
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• 2005

This paper presents an reduced-order near-optimal controller for the congestion control of Available Bit Rate (ABR) service in Asynchronous Transfer Mode (ATM) networks. We introduce the model, of a class of ABR traffic, that can be controlled using a Explicit Rate feedback for congestion control in ATM networks. Since there are great computational complexities in the class of optimal control problem for the ABR model, the near-optimal controller via reduced-order technique is applied to this model. It is implemented by the help of weakly coupling and singular perturbation theory, and we use bilinear transformation because of its computational convenience. Since the bilinear transformation can convert discrete Riccati equation into continuous Riccati equation, the design problems of optimal congestion control can be reduced. Using weakly coupling and singular perturbation theory, the computation time of Riccati equations can be saved, moreover the real-time congestion control for ATM networks can be possible.

• East Asian mathematical journal
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• v.16 no.2
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• pp.267-275
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• 2000

In this paper, we study the duality theory of nonlinear parabolic systems. The main objective is to prove the duality theorem under general conditions within an infinite-dimensional framework. As an application, an example is given.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.436-439
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• 1992

A tubular reactor model represented by partial differential equations was studied as one of nonlinear distributed parameter optimal control problems. An optimal control theory in the form of maximum principles based on nonlinear integral equations was used to develop an algorithm to solve the problem.