• Title, Summary, Keyword: receding horizon control

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Receding Horizon Control (이동구간 제어기법)

  • 권욱현;안춘기
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.3
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    • pp.177-185
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    • 2003
  • Current issues of receding horizon control scheme are reviewed. The basic idea of receding horizon control is presented first. For unconstrained and constrained systems, the results of closed-loop stability in receding horizon control are surveyed. We investigate the two categories of robustness of receding horizon control : stability robustness and performance robustness. The existing optimization algorithm to solve receding horizon control problem is briefly mentioned. It is shown that receding horizon control has been extended to nonlinear systems without losing good properties such as stability and robustness. Many industrial applications are reported along with extensive references related to receding horizon control.

Stability of intervalwise receding horizon control for linear tie-varying systems

  • Ki, Ki-Baek;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • pp.430-433
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    • 1997
  • In this paper, an intervalwise receding horizon control (IRHC) is proposed which stabilizes linear continuous and discrete time-varying systems each other by means of a feedback control stemming from a receding horizon concept and a minimum quadratic cost. The results parallel those obtained for continuous [4],[9] and discrete time varying system [5],[15] each other.

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Some Properties on Receding Horizon $H_{\infty}$ Control for Nonlinear Discrete-time Systems

  • Ahn, Choon-Ki;Han, Soo-Hee;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • pp.460-465
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    • 2004
  • In this paper, we present some properties on receding horizon $H_{\infty}$ control for nonlinear discrete-time systems. First, we propose the nonlinear inequality condition on the terminal cost for nonlinear discrete-time systems. Under this condition, noninceasing monotonicity of the saddle point value of the finite horizon dynamic game is shown to be guaranteed. We show that the derived condition on the terminal cost ensures the closed-loop internal stability. The proposed receding horizon $H_{\infty}$ control guarantees the infinite horizon $H_{\infty}$ norm bound of the closed-loop systems. Also, using this cost monotonicity condition, we can guarantee the asymptotic infinite horizon optimality of the receding horizon value function. With the additional condition, the global result and the input-to-state stable property of the receding horizon value function are also given. Finally, we derive the stability margin for the saddle point value based receding horizon controller. The proposed result has a larger stability region than the existing inverse optimality based results.

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Receding horizon tracking controller and its stability properties

  • Kwon, Wook-Hyun;Byun, Dae-Gyu
    • 제어로봇시스템학회:학술대회논문집
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    • pp.801-806
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    • 1987
  • The receding horizon tracking control for the discrete time invariant systems is presented in this paper. This control law is derived with the receding horizon concept from the standard tracking problems. Stability properties of this control law are analyzed. It is shown that there exists a finite horizon index for which the closed loop systems are always asymptotically stable. The receding horizon tracking control is a kind of predictive control and will add a new clan to many existing predictive controls, with which some comparisons are made.

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Some Recent Results of Approximation Algorithms for Markov Games and their Applications

  • 장형수
    • Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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    • pp.15-15
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    • 2003
  • We provide some recent results of approximation algorithms for solving Markov Games and discuss their applications to problems that arise in Computer Science. We consider a receding horizon approach as an approximate solution to two-person zero-sum Markov games with an infinite horizon discounted cost criterion. We present error bounds from the optimal equilibrium value of the game when both players take “correlated” receding horizon policies that are based on exact or approximate solutions of receding finite horizon subgames. Motivated by the worst-case optimal control of queueing systems by Altman, we then analyze error bounds when the minimizer plays the (approximate) receding horizon control and the maximizer plays the worst case policy. We give two heuristic examples of the approximate receding horizon control. We extend “parallel rollout” and “hindsight optimization” into the Markov game setting within the framework of the approximate receding horizon approach and analyze their performances. From the parallel rollout approach, the minimizing player seeks to combine dynamically multiple heuristic policies in a set to improve the performances of all of the heuristic policies simultaneously under the guess that the maximizing player has chosen a fixed worst-case policy. Given $\varepsilon$>0, we give the value of the receding horizon which guarantees that the parallel rollout policy with the horizon played by the minimizer “dominates” any heuristic policy in the set by $\varepsilon$, From the hindsight optimization approach, the minimizing player makes a decision based on his expected optimal hindsight performance over a finite horizon. We finally discuss practical implementations of the receding horizon approaches via simulation and applications.

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Input Constrained Receding Horizon Control Using Complex Polyhedral Invariant Region (복소형 다각형 불변영역을 이용한 입력제한 예측제어)

  • 이영일;방대인;윤태웅;김기용
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.12
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    • pp.991-997
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    • 2002
  • The concept of feasible & invariant region plays an important role to derive closed loop stability and achie adequate performance of constrained receding horizon predictive control. In this paper, we define a complex polyhedral feasible & invariant set for all stabilizable input-constrained linear systems by using a complex transform and propose a one-norm based receding horizon control scheme using these invariant sets. In order to get a larger stabilizable set, a convex hull of invariant sets which are defined for different state feedback gains is used as a target invariant set of the constrained receding horizon control. The proposed constrained receding horizon control scheme is formulated so that it can be solved via linear programming.

A receding horizon guidance law considering autopilot lag (자동조종장치 지연을 고려한 미사일의 이동구간 유도법칙)

  • Han, Chang-Woon
    • Proceedings of the KIEE Conference
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    • pp.115-118
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    • 2003
  • In recent years, a receding horizon guidance law based on receding horizon control and optimal control is proposed. A receding horizon guidance law considering autopilot lag and constraints is proposed. The performance of receding horizon guidance law in the presence of target maneuvers is confirmed by simulation results. Through many simulation, a suitable selection of weighting matrix can minimize effect of disturbance, target acceleration. which is meaning of this paper.

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Feedback stabilization of linear systems with delay in control by receding horizon (지연요소를 갖는 시스템의 안정화 방법)

  • 권욱현
    • 전기의세계
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    • v.28 no.5
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    • pp.44-48
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    • 1979
  • For ordinary systems the receding horizon method has beer proved by the author as a very useful and easy tool to find stable feedback controls. In this paper an open-loop optimal control which minimizes the control energy with a suitable upper limit and terminal control and state constraints is derived and then transformed to the closed-loop control. The stable feedback control law is obtained from the closed-loop control. The stable feedback control law is obtained from the closed-loop control by the receding horizon concept. It is shown by the Lyapunov method that the control law derived from the receding, horizon concept is asymtotically stable under the complete controllability condition. The stable feedback control which is similar to but more general than the receding horizon control is presented in this paper To the author's knowledge the control laws in this paper are easiest to stabilize systems with delay in control.

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A Decentralized Approach to Power System Stabilization by Artificial Neural Network Based Receding Horizon Optimal Control (이동구간 최적 제어에 의한 전력계통 안정화의 분산제어 접근 방법)

  • Choi, Myeon-Song
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.7
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    • pp.815-823
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    • 1999
  • This study considers an implementation of artificial neural networks to the receding horizon optimal control and is applications to power systems. The Generalized Backpropagation-Through-Time (GBTT) algorithm is presented to deal with a quadratic cost function defined in a finite-time horizon. A decentralized approach is used to control the complex global system with simpler local controllers that need only local information. A Neural network based Receding horizon Optimal Control (NROC) 1aw is derived for the local nonlinear systems. The proposed NROC scheme is implemented with two artificial neural networks, Identification Neural Network (IDNN) and Optimal Control Neural Network (OCNN). The proposed NROC is applied to a power system to improve the damping of the low-frequency oscillation. The simulation results show that the NROC based power system stabilizer performs well with good damping for different loading conditions and fault types.

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Optimal Feedback Control of Available Bit Rate Traffic in ATM using Receding Horizon Control

  • Shin, Soo-Young;Kwon, Wook-Hyun
    • Proceedings of the IEEK Conference
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    • pp.133-136
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    • 2001
  • In this work, the problem of regulating and tracking available bit rate (ABR) traffic in ATM network. The issue of providing control signals to throttled sources at distant location from bottlenecked node is of particular interest. Network modeling and design of controller is outlined. To obtain optimal control, receding horizon control (RHC) theory is applied. Simulation results are presented in views of regulation and tracking problems with or without constraints.

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