• Title/Summary/Keyword: Optimal Control

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Optimal Control of Time and Energy for Mobile Robots Using Genetic Algorithm (유전알고리즘을 이용한 이동로봇의 시간 및 에너지 최적제어)

  • Park, Hyeon-jae;Park, Jin-hyun;Choi, Young-kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.4
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    • pp.688-697
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    • 2017
  • It is very difficult to solve mathematically the optimal control problem for non - linear mobile robots to move to target points with minimum energy related to velocity, acceleration and angular velocity in minimum time. This paper proposes a method to obtain optimal control gains with which mobile robots move with minimum energy related to velocity, acceleration and angular velocity in minimum time using genetic algorithms. Mobile robots are non - linear systems so that their optimal control gains depend on initial positions. Hence initial positions are divided into some partition points and optimal control gains are obtained at each partition point with genetical algorithms. These optimal control gains are used to train neural networks that generate proper control gains at arbitrary initial position. Finally computer simulation studies have been conducted to verify the effectiveness of the method proposed in this paper.

Anti-Sway Control of a Jib Crane Using Time Optimal Control (시간최적제어를 이용한 지비크레인의 흔들림제어)

  • KANG MIN-WOO;HONG KEUM-SHIK
    • Journal of Ocean Engineering and Technology
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    • v.19 no.1
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    • pp.87-94
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    • 2005
  • This paper investigates the constant-level luffing and time optimal control of jib cranes. The constant-level luffing, which is the sustainment of the load at a constant height during luffing, is achieved by analyzing the kinematic relationship between the angular displacement of a boom and that of the main hoist motor of a jib crane. Under the assumption that the main body of the crane does not rotate, the equations of motion of the boom are derived using Newton's Second Law. The dynamic equations for the crane system are highly nonlinear; therefore, they are linearized under the small angular motion of the load to apply linear control theory. This paper investigates the time optimal control from the perspective of no-sway at a target point. A stepped velocity pattern is used to design the moving path of the jib crane. Simulation results demonstrate the effectiveness of the time optimal control, in terms of anti-sway motion of the load, while luffing the crane.

The Application of Optimal Control Through Fiscal Policy on Indonesian Economy

  • SYAHRINI, Intan;MASBAR, Raja;ALIASUDDIN, Aliasuddin;MUNZIR, Said;HAZMI, Yusri
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.741-750
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    • 2021
  • The budget deficit is closely related to expansionary fiscal policy as a fiscal instrument to encourage economic growth. This study aims to apply optimal control theory in the Keynesian macroeconomic model for the economy, so that optimal growth can be found. Macroeconomic variables include GDP, consumption, investment, exports, imports, and budget deficit as control variables. This study uses secondary data in the form of time series, the time period 1990 to 2018. Performing optimal control will result in optimal fiscal policy. The optimal determination is done through simulation, for the period 2019-2023. The discrete optimal control problem is to minimize the objective function in the form of a quadratic function against the deviation of the state variable and control variable from the target value and the optimal value. Meanwhile, the constraint is Keynes' macroeconomic model. The results showed that the optimal value of macroeconomic variables has a deviation from the target values consisting of: consumption, investment, exports, imports, GDP, and budget deficit. The largest deviation from the average during the simulation occurs in GDP, followed by investment, exports, and the budget deficit. Meanwhile, the lowest average deviation is found in imports.

Investigations on Dynamic Trading Strategy Utilizing Stochastic Optimal Control and Machine Learning (확률론적 최적제어와 기계학습을 이용한 동적 트레이딩 전략에 관한 고찰)

  • Park, Jooyoung;Yang, Dongsu;Park, Kyungwook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.4
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    • pp.348-353
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    • 2013
  • Recently, control theory including stochastic optimal control and various machine-learning-based artificial intelligence methods have become major tools in the field of financial engineering. In this paper, we briefly review some recent papers utilizing stochastic optimal control theory in the fields of the pair trading for mean-reverting markets and the trend-following strategy, and consider a couple of strategies utilizing both stochastic optimal control theory and machine learning methods to acquire more flexible and accessible tools. Illustrative simulations show that the considered strategies can yield encouraging results when applied to a set of real financial market data.

Robust Optimal Control of Robot Manipulators with a Weighting Matrix Determination Algorithm

  • Kim, Mi-Kyung;Kang, Hee-Jun
    • 제어로봇시스템학회:학술대회논문집
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    • pp.2004-2009
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    • 2003
  • A robust optimal control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method finding the Q weighting matrix is shown. Computer simulations have been done for a weight-lifting operation of a two-link manipulator and the result of the simulation shows that the proposed algorithm is very effective for a robust control of robotic systems.

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Optimal Control of Speed Regulating Systems (속도제어를 대상으로 하는 계통의 최적제어)

  • 양흥석;이종호
    • 전기의세계
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    • v.28 no.2
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    • pp.55-60
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    • 1979
  • In this paper, a new method of the optimal control of the regulator and tracking control problem concerning the dimension of the velocity is derived and applied for the second order plant. The output position, output velocity and the control effort are plottcd with time applying analog computer simulation. And it is compared with the output of the ordinary optimal control law in case the reference input is given by velocity function, and studied about the gain of this method.

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An Optimal Control Approach to Robust Control of Robot Manipulators (로봇 매니퓰레이터의 강인제어를 위한 최적제어로의 접근)

  • 김미경;강희준
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.12
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    • pp.176-182
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    • 2003
  • An optimal control approach to robust control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method to find the matrix is shown. Simulations are made for a weight-lifting operation of a two-link manipulator and the robust control performance of robotic systems by the proposed algorithm is remarkable.

Target Pointing Guidance using Optimal Control (최적제어를 이용한 목표점 지향 유도)

  • Whang, Ick-Ho
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.7
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    • pp.881-888
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    • 1999
  • Target pointing guidance steers a vehicle to point at a target point at a given range Rs. In this paper, vehicle's motions relative to the target point are modeled by differential equations. Then a target pointing guidance law is derived using optimal control theories. In addition, it is shown that the proposed guidance law can achieve the goal of target pointing guidance whatever initial headings are.

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DUALITY IN THE OPTIMAL CONTROL PROBLEMS FOR HYPERBOLIC SYSTEMS

  • Kim, Hyun-Min;Park, Jong-Yeoul;Park, Sun-Hye
    • 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.

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A study on the operation performance control of urban rail vehicle using an optimal control (최적제어를 이용한 도시철도 차량 주행제어 연구)

  • Tak Kil Hun;Kim Dong-Hwan;Kim Chi Tae
    • Proceedings of the KSR Conference
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    • pp.107-112
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    • 2005
  • When it comes to automatic operation control of urban rail vehicle, a PID control makes it run between stations within the fixed time and stop exactly at the stop sign on the platform, satisfying jerk limit. An optimal control is applied to automatic operation performance control to minimize energy consumption while the urban rail vehicle satisfies automatic operation condition on this paper. The control performance in terms of energy minimization along with the constraint on precision stops is compared between the optimal control and PID control.

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