• 제어로봇시스템학회논문지
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• 제9권3호
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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.

• 대한안전경영과학회지
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• 제19권3호
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• pp.89-95
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• 2017

This paper presents another maintenance policy for a group of units under finite operating horizon. A group of identical units are subject to random failures. Group maintenances are performed to all units together at specified intervals, and the failed units during operation are remained idle until the next group maintenance set-up. Unlike the traditional assumption of infinite operating horizon, we adopt the assumption of the finite operating horizon which reflect the rapid industrial advance and short life cycle of modern times. The units are under operation until the end of the operating horizon. Further, the operation of units are extended to the first group maintenance time after the end of the horizon. The total cost under the proposed maintenance policy is derived. The optimal group maintenance interval and the expected number of group maintenances during the horizon are found. It is shown that the proposed policy is better than the classical group maintenance policy in terms of total cost over the operating horizon. Numerical examples are presented for illustrations.

• 한국전산응용수학회:학술대회논문집
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• 한국전산응용수학회 2003년도 KSCAM 학술발표회 프로그램 및 초록집
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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.

• 한국환경과학회지
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• 제28권8호
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• pp.655-667
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• 2019

This research aims to identify the possibility of developing A horizon resources that can be used for construction and civil engineering work. As such, the utility of A horizon resources was examined by establishing planting ground through a mixture of soil layers and by analyzing the growth and development of Pinus densiflora. The physicochemical and physical properties of the soil were as follows: the A horizon was sandy clay loam, B horizon was sandy loam, and the mixture of two layers appeared as sandy loam, which was identical to the B horizon. The experimental groups did not show any significant difference in their physical properties of porosity and degree of water-stable aggregates. With regards to chemical properties, the A horizon as well as the mixture of A and B horizon showed acidity while the B horizon showed alkalinity. The figures of organic matter, total nitrogen, available phosphate, and replaceable potassium were greater as the A horizon content increased, whereas the figures of replaceable calcium, replaceable magnesium, and conductivity increased as the A horizon content decreased. As a result of the growth and development of Pinus densiflora in each planting ground, the final survival rates were all above 100%. However, the tree height and the rate of growth for the diameter of root were higher in the order of A horizon > A horizon + B horizon > B horizon,indicating that the increased A horizon content is related to the growth and development of Pinus densiflora. The treatment of soil with improvement agents, used to recover the functions of in-situ soil showing poor growth and development, did not have a clear impact on the soil texture and porosity. However, the degree of water-stable aggregates increased significantly when using O horizon as the soil improvement agent among the types of in-situ soil. In contrast, all items related to the chemical properties showed significant differences following the treatment by soil improvement agents. The survival rate according to the treatment of soil improvement agents for the growth and development of Pinus densiflora was higher in the order of organic horizon = no treatment > compound fertilizer > organic fertilizer + compound fertilizer > organic fertilizer; this result was statistically significant with a marginal significance value of the log-rank test(p < 0.05).

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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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.

• 산업공학
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• 제16권4호
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• pp.441-449
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• 2003

In this paper we propose a distribution planning method aiming the use in the real-life situations. The assumed form of the distribution network is arborescence. At every node in the distribution network, orders are placed periodically. At each renewal of planning horizon, demand informations of periods in the horizon are updated. The objective of the problem is to minimize the total cost, which is the sum of holding and backorder costs of all sites during planning horizon. For such a situation, this study addressed an effective distribution plan when demands for demand-sites are provided for a given planning horizon.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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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.

• 대한산업공학회지
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• 제20권1호
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• pp.121-131
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• 1994

Since many infinite horizon problems have infinite sequence of data to be considered, in general, it is impossible to express the optimal strategies finitely or to calculate them in finite time. This paper considers undiscounted nonhomogeneous deterministic infinite horizon problems. For those problems, we take a basic step to solve this class of infinite horizon problems optimally by giving a sufficient condition for a finite solution.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집(한일합동학술편); 한국과학기술대학, 충남; 16-17 Oct. 1987
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.535-535
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• 2000

This paper presents an adaptive receding horizon H$_{\infty}$ controller for the linear parameter varying systems in the deterministic environment, which combines a parameter range estimator and a robust receding horizon H$_{\infty}$ controller using the parameter bounds. Using parameter set inclusion and terminal inequality condition, the closed-loop system stability is guaranteed. It is shown that the stabilizing adaptive receding horizon H$_{\infty}$ controller guarantees the H$_{\infty}$ norm bound.