• Title/Summary/Keyword: Optimal Control Gain

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Neighboring Optimal Control using Pseudospectral Legendre Method (Pseudospectral Legendre법을 이용한 근접 최적 제어)

  • 이대우;조겸래
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.7
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    • pp.76-82
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    • 2004
  • The solutions of neighboring optimal control are typically obtained using the sweep method or transition matrices. Due to the numerical integration, however, the gain matrix can become infinite as time go to final one in the transition matrices, and the Riccati solution can become infinite when the final time free. To overcome these disadvantages, this paper proposes the pseudospectral Legendre method which is to first discreteize the linear boundary value problem using the global orthogonal polynomial, then transforms into an algebraic equations. Because this method is not necessary to take any integration of transition matrix or Riccati equation, it can be usefully used in real-time operation. Finally, its performance is verified by the numerical example for the space vehicle's orbit transfer.

Design of Fuzzy Scaling Gain Controller using Genetic Algorithm (유전자 알고리즘을 이용한 퍼지 스케일링 게인 제어기의 설계)

  • Shin, Hyun-Seok; Kho, Jae-Won;Kwon, Cheol;Park, Mig-Non
    • Proceedings of the KIEE Conference
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    • 1998.07g
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    • pp.2268-2271
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    • 1998
  • This paper proposes a method which can resolve the problem of existing fuzzy Pl controller using optimal scaling gains obtained by genetic algorithm. The new method adapt a fuzzy logic controller as a high level controller to perform scaling gain algorithm between two pre-determined sets.

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Speed Control of AC Servo Motor Using Adaptive Fuzzy-Sliding Observer (적응 퍼지-슬라이딩 관측기를 이용한 교류 서보 전동기 속도제어)

  • Kim, Sang-Hoon;Yoon, Kwang-Ho;Ko, Bong-Woon;Kim, Won-Tae;Kim, Gi-Nam;Nam, Moon-Hyon;Kim, Lark-Kyo
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.726-728
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    • 2004
  • In this paper, the gain of the observer is properly set up using the fuzzy control and Fuzzy-Sliding observer(FSQ) that have a superior transient characteristic and is easy to implement compared to the existing method is designed. It estimate the differentiation of the armature current directly using the armature current measured in the AC motor. It estimate the speed of the rotor using the differentiation. It is proposed speed sensorless control method using the estimated speed. Optimal gain of speed observer(Luenberger observer) was set up using the fuzzy control and adapted speed control of AC servo motor. To verify the performance of designed Fuzzy-Sliding observer, simulation compared with fixed speed observer gain of G.B Wang and S.S Peng's sliding observer is performed. Also, it was proved the excellence and feasibility of the proposed observer from the comparison test with a speed sensor and without a speed sensor which used a highly efficient drive and 400W AC servo motor starting system.

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Sliding Mode Controller with Sliding Perturbation Observer Based on Gain Optimization using Genetic Algorithm

  • You, Ki-Sung;Lee, Min-Cheol;Yoo, Wan-Suk
    • Journal of Mechanical Science and Technology
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    • v.18 no.4
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    • pp.630-639
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    • 2004
  • The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observe. (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.

A study on the stabilizing control of uncertain system with optimal control (최적제어이론을 이용한 불확실한 시스템의 제어 기법 연구)

  • 한형석;이장규
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.55-59
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    • 1991
  • This paper presents a method for designing a full state feedback linear static control law. This will stabilize a given linear uncertain system and also guarantee the performance of the system. The uncertain systems are described by state equation which contains uncertain parameters in system and input distribution matrices. The method is based on the guaranteed cost control of Chang and Peng(1972). The controller gain can be obtained by the solution of a algebraic Riccati equation in which the input weighting matrices depend on the uncertainty bounds. The algebraic Riecati equation in this paper is same as that of weighted LQ regulator problem.

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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.

Self-Tuning Controller design for the motion control of a Single Rod Hydraulic Cylinder (편로드 유압실린더의 운동제어를 위한 자기동조 제어기설계)

  • 김정태;김문생
    • Journal of KSNVE
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    • v.8 no.3
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    • pp.441-449
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    • 1998
  • A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

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Torque Control of Wind Turbine Using Nonlinear Parameter of Rotor Speed in the Region of Optimal Tip Speed Ratio (최적 주속비 구간에서 로터속도 비선형 파라미터를 이용한 풍력터빈의 토크제어)

  • Lim, Chae-Wook;Kim, Sang-Gyun
    • The KSFM Journal of Fluid Machinery
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    • v.15 no.2
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    • pp.30-35
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    • 2012
  • Aerodynamic torque of wind turbine has nonlinear properties. Nonlinearity of aerodynamic torque is very important in wind turbine in the aspect of control. The traditional torque control method using optimal mode gain has been applied in many wind turbines but its response is slower as wind turbine size is larger. In this paper, a torque control method using a nonlinear parameter of rotor speed among nonlinear properties of aerodynamic torque. Simulink model is implemented to obtain the nonlinear parameter of rotor speed and numerical simulations for a 2MW wind turbine are carried out and simulation results for the traditional and proposed torque control methods are compared.

Closed-loop predictive control using periodic gain

  • Lee, Young-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.173-176
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    • 1994
  • In this paper a closed-form predictive control which takes the intervalwise receding horizon strategy is presented and its stability properties are investigated. A slate-space form output predictor is derived which is composed of the one-step ahead optimal output prediction, input and output data of the system. A set of feedback gains are obtained using the dynamic programming algorithm so that they minimize a multi-stage quadratic cost function and they are used periodically.

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A study of ball-beam system control using genetic algorithms (유전자 알고리즘을 이용한 Ball-Beam 시스템의 제어에 관한 연구)

  • Lee, Nam-Gi;Park, Jong-Beom;Cho, Hwang
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.968-971
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    • 1996
  • In this paper, feedback controller is designed for ball-beam system using genetic algorithms. A genetic algorithms are implemented for optimizing gain parameters of feedback controller. We can find optimal point in multi-dimensional search space by using genetic algorithms. Performance of controller is tested by simulation of ball-beam system.

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