• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.130-130
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• 2000

This paper presents a robust fault diagnosis and fault tolerant control lot the actuator and sensor faults in the closed-loop systems affected by unknown inputs or disturbances. The fault diagnostic scheme is based on the residual set generation by using robust Parity space approach. Residual set is evaluated through the threshold test and then fault is isolated according to the decision logic table. Once the fault diagnosis module indicates which actuator or sensor is faulty, the fault magnitude is estimated by using the disturbance-decoupled optimal state estimation and a new additive control law is added to the nominal one to override the fault effect on the system. Simulation results show that the method has definite fault diagnosis and fault tolerant control ability against actuator and sensor faults.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.795-797
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• 1998

This paper suggests a design method of the optimal PD control system having robust performance. This PD control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of proportional(P) gain and derivative(D) gain that are given by PD servo controller. These proportional and derivative gains are simultaneously optimized in the search domain guaranteeing the robust performance of closed-loop system. This PD control system is applied to the fuel-injection control system of diesel engine and compared with ${\mu}$ -synthesis control system for robust performance. The effectiveness of this PD control system is verified by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.1004-1014
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• 2007

In sensor networks, it is crucial to reliably and energy-efficiently deliver sensed information from each source to a sink node. Specifically, in mobile sink (user) applications, due to the sink mobility, a stationary dissemination path may no longer be effective. The path will have to be continuously reconfigured according to the current location of the sink. Moreover, the dynamic optimal path from each source to the sink is required in order to reduce end-to-end delay and additional energy wastage. In this paper, an Adaptive Reversal Optimal path Tree (AROT) protocol is proposed. Information delivery from each source to a mobile sink can be easily achieved along the AROT without additional control overhead, because the AROT proactively performs adaptive sink mobility management. In addition, the dynamic path is optimal in terms of hop counts and the AROT can maintain a robust tree structure by quickly recovering the partitioned tree with minimum packet transmission. Finally, the simulation results demonstrate that the AROT is a considerably energy-efficient and robust protocol.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.27.4-27
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• 2001

A stabilizing control method for linear systems with model uncertainties and hard input constraints is developed, which does not require on-line optimizations. This work is motivated by the constrained robust MPC(CRMPC) approach [3] which adopts the dual mode prediction strategy (i.e. free control moves and invariant set) and minimizes a worst case performance criterion. Based on the observation that, a feasible control sequence for a particular state can be found as a linear combination of feasible sequences for other states, we suggest a stabilizing control algorithm providing sub-optimal and feasible control sequences using pre-computed optimal sequences for some canonical states. The on-line computation of the proposed method reduces to simple matrix multiplication.

• IE interfaces
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• v.22 no.1
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• pp.95-103
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• 2009

During the past few years, design of experiments (DOE) has been gaining acceptance in the telecommunications research community as a mean for designing and analyzing experiments economically and efficiently. In addition, the need for introducing a systematic robust design methodology (i.e., one of the most popular DOE methodologies) to network simulations has been increasing. In this paper, we present an architecture of voice over IP (VoIP) application and the E-Model for calculating the perceived quality of service (QoS). Then, we apply the Taguchi robust design methodology to optimize the perceived QoS of VoIP application, and describe the detailed step-by-step procedures. We have used ns-2 simulator to collect experimental data in which the SN ratio, a robustness measure, is analyzed to determine an optimal design condition. The analysis shows that "initial delay time in playout buffer" is a major control factor for ensuring robust behaviors of the perceived QoS of VoIP. Finally, we verify the proposed optimal design condition using a confirmation experiment.

• Transactions of The Korea Fluid Power Systems Society
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• v.7 no.3
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• pp.20-27
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• 2010

A vehicle suspension system performs two functions, the ride quality and the stability, which conflict with each other. An active suspension system has an external energy source, from which energy is always supplied to the system for continuous control of vehicle motion. Therefore, an active suspension system can have even more improved performance. Some control laws have been proposed for active suspension system, but in this paper, an optimal variable structure control(VSC) is proposed. The VSC method is well suited for a class of nonlinear system and can address the robustness issues to constant modelling errors and disturbances. This paper develops an optimal VSC controller and compares its performance to those of a passive suspension system and an active suspension system with an optimal controller. The transient and frequency responses are analyzed respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.46-51
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• 1997

The optimal control of a continuous process has been performed using genetic algorithms(GAs). GAs are robust and easily applicable for complex and highly nonlinear problems. We introduce the heuristics 'dynamic range' which reduces the search space dramaticaly keeping the robust search of GAs. GAs with dynamic range show the better performance than SQP(Successive Quadratic Programing) method which converges to a local minimum. The proposed methology has been applied to the optimal control of the continuous MMA-VA copolymerization reactor for the production of the desired molecular wieght and the composition of VA in dead copolymer.

• Earthquakes and Structures
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• v.1 no.3
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• pp.289-306
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• 2010

A gradient-based evolutionary optimization methodology is presented for finding the optimal design of viscous dampers to minimize an objective function defined for a linear multi-storey structure. The maximum value along height of the transfer function amplitudes for the interstorey drifts is taken as the objective function. Since the ground motion includes various uncertainties, the optimal damper placement may be different depending on the ground motion used for design. Furthermore, the transfer function treated as the objective function depends on the properties of structural parameters and added dampers. This implies that a more robust damper design is desired. A reliable and robust damping design system against any unpredictable ground motions can be provided by minimizing the maximum transfer function. Such design system is proposed in this paper.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.207-212
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• 2008

This paper presents a robust and computationally efficient optimal design algorithm for electromagnetic devices by combining an adaptive response surface approximation of the objective function and($1+{\lambda}$) evolution strategy. In the adaptive response surface approximation, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design with the Max Distance and Min Distance criteria. The proposed algorithm is applied to an analytic example and TEAM problem 22, and its robustness and computational efficiency are investigated.

• Journal of the Korean Mathematical Society
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• v.59 no.6
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• pp.1153-1170
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• 2022

In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.