• Advances in Computational Design
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• v.5 no.3
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• pp.233-260
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• 2020

The main purpose to introduce model based controller in proposed control technique is to provide better and fast learning of the floating dynamics by means of fuzzy logic controller and also cancelling effect of nonlinear terms of the system. An iterative adaptive dynamic programming algorithm is proposed to deal with the optimal trajectory-tracking control problems for autonomous underwater vehicle (AUV). The optimal tracking control problem is converted into an optimal regulation problem by system transformation. Then the optimal regulation problem is solved by the policy iteration adaptive dynamic programming algorithm. Finally, simulation example is given to show the performance of the iterative adaptive dynamic programming algorithm.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.399-409
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• 2007

In this paper we use iterative dynamic programming in the discrete case to solve a wide range of the nonlinear equations systems. First, by defining an error function, we transform the problem to an optimal control problem in discrete case. In using iterative dynamic programming to solve optimal control problems up to now, we have broken up the problem into a number of stages and assumed that the performance index could always be expressed explicitly in terms of the state variables at the last stage. This provided a scheme where we could proceed backwards in a systematic way, carrying out optimization at each stage. Suppose that the performance index can not be expressed in terms of the variables at the last stage only. In other words, suppose the performance index is also a function of controls and variables at the other stages. Then we have a nonseparable optimal control problem. Furthermore, we obtain the path from the initial point up to the approximate solution.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.465-472
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• 2004

Analog CPPN-based optimal road boundary detection algorithm for autonomous vehicle is proposed. The CPPN is a massively connected analog parallel array processor. In the paper, the dynamic programming which is an efficient algorithm to find the optimal path is implemented with the CPPN algorithm. If the image of road-boundary information is utilized as an inter-cell distance, and goals and start lines are positioned at the top and the bottom of the image, respectively, the optimal path finding algorithm can be exploited for optimal road boundary detection. By virtue of the parallel and analog processing of the CPPN and the optimal solution of the dynamic programming, the proposed road boundary detection algorithm is expected to have very high speed and robust processing if it is implemented into circuits. The proposed road boundary algorithm is described and simulation results are reported.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.726-733
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• 2004

This paper presents a method to segment object ID(identification) marks on poor quality images under uncontrolled lighting conditions of automated inspection process. The method is based on dynamic programming using multiple templates and normalized gray-level correlation (NGC) method. If the lighting condition is not good and hence, we can not control the image quality, target image to be inspected presents poor quality ID marks and it is not easy to identify and recognize the ID characters. Conventional several methods to segment the interesting ID mark regions fail on the bad quality images. In this paper, we propose a multiple template method, which uses combinational relation of multiple templates from model templates to match several characters of the inspection images. To increase the computation speed to segment the ID mark regions, we introduce the dynamic programming based algorithm. Experimental results using images from real factory automation(FA) environment are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.397-404
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• 2011

This paper proposes an algorithm capable of extracting corresponding points between a pair of stereo images based on dynamic programming. The purpose of extracting the corresponding points is to provide the stereo disparity data to a road-slope estimation algorithm with high accuracy and in real-time. As the road-slope estimation algorithm does not require dense disparity data, the proposed stereo matching algorithm aims at extracting corresponding points accurately and quickly. In order to realize this contradictory goal, this paper exploits dynamic programming, and minimizes matching candidates using vertical components of color edges. Furthermore, the typical occlusion problem in stereo vision is solved. The proposed algorithm is proven to be effective through experiments with various images captured on the roads.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.805-807
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• 2005

본 논문에서는 동적 계획법(dynamic programming)과 이미지 세그먼트(segment)를 이용한 새로운 스테레오 정합(stereo matching)기법을 제안한다. 일반적으로 동적 계획법(dynamic programming)은 빠르면서도 비교적 정확하고, 조밀(dense)한 disparity map을 얻을 수 있다. 그러나 경계(boundary)근처의 폐색지역(occlusion region)이나, 텍스쳐가 적은 모호한 영역에서는 잘못된 결과를 유도할 수 있다. 본 논문에서는 이러한 문제점들을 해결하기 위해 먼저 이미지를 아주 작은 영역으로 분할(over-segmentation)하고, 이런 작은 영역들이 비슷한 disparity를 가질 것이라고 가정한다. 다음으로 동적 계획법(dynamic programming)을 통해 정합을 수행한다. 여기서 계산비용(cost)은 기존의 정합윈도우 안에서 세그먼트 영역을 적용한 새로운 비용함수를 사용하며, 이 새로운 비용함수를 통해 정확도를 높인다. 마지막으로 동적 계획법을 통하여 얻어진 조밀한 disparity map을 세그먼트 영역들의 시각특성(visibility)과 유사도(similarity)를 이용하여 에러를 찾아내고, 세그먼트 정합을 통해 수정함으로 정확한 disparity map을 찾아낸다.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.1
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• pp.99-105
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• 2012

Track-before-detect techniques based on dynamic programming have provided solutions for detecting targets from a sequence of images. In its application to airborne threat detection, dynamic programming solutions should take into account the distinguishable properties of objects in a collision course. This paper describes the development of a new track scoring function that accumulates scores for airborne targets in Bayesian framework. Numerical results show that the proposed scoring function has slightly better detection capabilities.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.19-30
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• 2013

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.213-219
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• 2005

In order to move NPC's to target location at game maps, various algorithm including A* has been used. The most frequently used algorithm among them is A* with fast finding speed. But A* has the following problems. The first problem is that at randomly changing map, it is necessary to calculate all things again whenever there are any changes. And when calculation is wrong, it is not possible to search for target. The second problem is that it is difficult to move avoiding dangerous locations damaging NPC such as an obstruction. Although it is possible to avoid moving to locations with high weight by giving weight to dangerous factors. it is difficult to control in case NPC moves nearby dangerous factors. In order to solve such problems, in this thesis, the researcher applied Dynamic Programming to path-finding algorithm. As the result of its application, the researcher could confirm that the programming was suitable for changes at the map with random change and NPC's avoided the factors being dangerous to them far away. In addition. when compared to A*, there were good results.