• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.396-402
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• 2001

In various applications of queueing systems, admission control is often employed. It is known that the threshold-type of admission control is optimal in many practical applications despite its simplicity. However, determining the optimal threshold value is hard in general, because analytical expressions for the stationary queue length distributions are not easily available in most queueing systems. In this paper, to quickly determine the optimal threshold value under threshold-type admission control, we develop a concurrent simulation technique, which can save large amount of CPU time required in simulation, compared to the standard simulation procedure.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.12
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• pp.697-703
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• 2002

Interior permanent magnet synchronous motor(IPMSM) is widely used in many applications such as an electric vehicle, compressor drives of air conditioner and machine tool spindle drives. In order to maximize the efficiency in such applications, this paper is proposed the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to IPMSM drive system, the operating characteristics controlled by efficiency optimization control are examined in detail by simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.235-244
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• 2014

This article introduces recent trends in RHC (Receding Horizon Control), also known as MPC (Model Predictive Control), that has been well recognized in industry and academy as a systematic approach for optimal design and constraint management. Constrained and robust RHCs will be briefly reviewed with milestone results. Among the diverse developments and achievements of RHCs, implementation issues will be focused on, together with the latest applications. In particular, this article introduces results on how to solve a finite horizon open-loop optimal control problem in an efficient way, together with code generation for real-time execution and easy implementation. Instead of traditional applications such as refineries and petrochemical plants, this article highlights some selected emerging applications, such as energy management systems and mechatronics, that have resulted from state-of-the-art high performance computing power and advanced numerical schemes.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.498-502
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• 1986

A generalized singular linear quadratic control technique is developed to design an optimal trajectory tracking system. The output feedback control law is designed using this technique. The feedback gain matrix is synthesized to minimize tracking errors with pole placement capability to satisfy the control activity requirements. An applications to a bank-to-turn missile coordinated autopilot system design is presented.

• Nonlinear Functional Analysis and Applications
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• v.28 no.3
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• pp.659-670
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• 2023

In this paper, we study the distributed optimal control problem of a coupled system of the host-pathogen model. The system consists of the density of the susceptible host, the density of the infected host, and the density of pathogen particles. Our main goal is to minimize the infected density and also to decrease the cost of the drugs administered. First, we prove the existence and uniqueness of solutions for the proposed problem. Then, the existence of the optimal control is established and necessary optimality conditions are also derived.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.2
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• pp.74-82
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• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning control fuzzy neural network (AFLC-FNN) controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC-FNN controller. Also, this paper proposes speed control of IPMSM using AFLC-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled AFLC-FNN controller, the operating characteristics controlled by efficiency optimization control are examined in detail.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.412-430
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• 2003

In many practical problems in signal processing and control, the signal values are often restricted to belong to a finite number of levels. These questions are generally referred to as "finite alphabet" problems. There are many applications of this class of problems including: on-off control, optimal audio quantization, design of finite impulse response filters having quantized coefficients, equalization of digital communication channels subject to intersymbol interference, and control over networked communication channels. This paper will explain how this diverse class of problems can be formulated as optimization problems having finite alphabet constraints. Methods for solving these problems will be described and it will be shown that a semi-closed form solution exists. Special cases of the result include well known practical algorithms such as optimal noise shaping quantizers in audio signal processing and decision feedback equalizers in digital communication. Associated stability questions will also be addressed and several real world applications will be presented.

• 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.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.160-170
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• 2008

Temperature control of an enclosed thermal system which has many applications including Rapid Thermal Processing (RTP) of semiconductor wafers showed an input-constraint violation for nonlinear controllers due to inherent strong coupling between the elements [1]. In this paper, a constrained nonlinear optimal control design is developed, which accommodates input constraints using the linear algebraic equivalence of the nonlinear controllers, for the temperature control of an enclosed thermal process. First, it will be shown that design of nonlinear controllers is equivalent to solving a set of linear algebraic equations-the linear algebraic equivalence of nonlinear controllers (LAENC). Then an input-constrained nonlinear optimal controller is designed based on that LAENC using the constrained linear least squares method. Through numerical simulations, it is demonstrated that the proposed controller achieves the equivalent performances to the classical nonlinear controllers with less total energy consumption. Moreover, it generates the practical control solution, in other words, control solutions do not violate the input-constraints.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1143-1145
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• 2002

IPMSM (Interior Permanent Magnet Synchronous Motor) is widely used in many applications such as an electric vehicle, compressor drives of air conditioner and machine tool spindle drives. In order to maximize the efficiency in such applications, this paper is proposed the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The proposed control algorithm is applied to IPMSM drive system, the operating characteristics controlled by efficiency optimization control are examined in detail by simulation.