• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.172-176
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• 1989

In this paper, a simple method for designing iterative learning control scheme is proposed. The proposed learning algorithm is designed based on series expansion of inverse plant model. The proposed scheme has simple structure and fast convergency so that it is suitable for implementing it on conventional micro processor based controllers. The effectiveness of the proposed algorithm is investigated through a series of computer simulations.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.140-147
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• 2008

This paper describes a Neural Network based PD control scheme for motion control of pneumatic servo cylinder. Pneumatic systems have inherent nonlinearities such as compressibility of air and nonlinear frictions present in cylinder. The conventional linear controller is limited in some applications where the affection of nonlinear factor is dominant. A self-excited oscillation method is applied to derive the dynamic design parameters of linear model. Based on the parameters thus identified, a PD feedback compensator is designed first and then a neural network is incorporated. The experiments of a trajectory tracking control using the proposed control scheme are performed and a significant reduction in tracking error is achieved by comparing with those of a PD control.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.444-449
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• 2001

There have been many accidents of passenger ships on the sea and they have caused a big loss of human lives. Maritime Safety Committee(MSC) of International Maritime Organization(IMO) made evacuation analysis of Ro-Ro passenger ships mandatory in order to save as many lives as possible at the time of accident. But this is a temporary regulation and HSC/IMO ties to introduce a performance-based regulation to improve the effect of regulation. Simulation-based evacuation analysis is the basis of performance-based regulation. In this paper, we performed a simulation-based evacuation analysis on a passenger ship, which is usually used in the plying between land and islands in Korea, with EXODUS system. Through inspecting the results from this analysis in more detail, we can make a proposal to improve the safety of passenger ship. Finally we describe the features of IMEX(Intelligent Model for Extrication Simulation), a new evacuation model being developed in KRISO.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.58-69
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• 2014

This paper proposes a method for predicting maximum friction coefficients and optimal slip ratios as optimal control parameters for traction control or slip control of autonomous mobile robots on rough terrain. This paper focuses on strength of ground surface which indicates different characteristics depending on material types on surface. Strength of various material types can be estimated by Willoughby sinkage model and by a developed testbed which can measure forces, velocities, and displacements generated by wheel-terrain interaction. Estimated strength is collaborated on building improved Brixius model with friction-slip data from experiments with the testbed over sand and grass material. Improved Brixius model covers widespread material types in outdoor environments on predicting friction-slip characteristics depending on strength of ground surface. Thus, a prediction model for obtaining optimal control parameters is derived by partial differentiation of the improved Brixius model with respect to slip. This prediction model can be applied to autonomous mobile robots and finally gives secure maneuverability on rough terrain. Proposed method is verified by various experiments under similar conditions with the ones for real outdoor robots.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.685-689
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• 2005

In this paper, we consider a robust output feedback model predictive controller(MPC) design for Wiener model. Nonlinearities that couldn't be represented in static nonlinearity block of Wiener model are regarded as uncertainties in linear block. An dynamic output feedback controller design method is presented for Wiener MPC. According to MPC algorithm, the control law is computed based on linear matrix inequality(LMI)at each sampling time by solving convex optimization. Also, a new parameter dependent Lyapunov function is proposed to get a less conservative condition. The results are illustrated with numerical example.

• The Journal of Information Technology
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• v.4 no.4
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• pp.15-24
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• 2001

In current role-based systems, security officers handle assignments of users to roles. This may increase management efforts in a distributed environment because of the continuous involvement from security officers. The role-based delegation provides a means for implementing RBAC in a distributed environment. The basic idea of a role-based delegation is that users themselves may delegate role authorities to other users to carry out some functions on behalf of the former. This paper presents a user-level delegation model, which is based on Extended Role-Based Access Control(ERBAC). ERBAC provides finer grained access control on the base of subject and object level than RBAC model.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.153-162
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• 2014

A novel robust $H_{\infty}$ switching tracking control design method with disturbance observer is proposed for the near space interceptor (NSI) with aerodynamic fins and reaction jets. Initially, the flight envelop of the NSI is divided into small subregions, and a slow-fast loop polytopic linear parameter varying (LPV) model is proposed, to approximate the nonlinear dynamic of the NSI, based on the Jacobian linearization and Tensor-Product (T-P) model transformation approach. A disturbance observer is then constructed, to estimate the modeled disturbance. Subsequently, based on the descriptor system method, a robust switching controller is developed, to ensure that the closed-loop descriptor system is stable with a desired $H_{\infty}$ disturbance attenuation level. Furthermore, the outcome of the proposed switching tracking control problem is formulated as a set of linear matrix inequalities (LMIs). Finally, simulation results demonstrate the effectiveness of the proposed design method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.762-771
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• 2005

In this paper, an efficient Adaptive quality-of-service (QoS) traffic control scheme with priority scheduling is proposed for the multimedia traffic transmission over wireless access networks. The objective of the proposed adaptive QoS control (AQC) scheme is to realize end-to-end QoS, to be scalable without the excess signaling process, and to adapt dynamically to the network traffic state according to traffic flow characteristics. Here, the reservation scheme can be used over the wireless access network in order to get the per-flow guarantees necessary for implementation of some kinds of multimedia applications. The AQC model is based on both differentiated service model with different lier hop behaviors and priority scheduling one. It consists of several various routers, access points, and bandwidth broker and adopts the IEEE 802.1 le wireless radio technique for wireless access interface. The AQC scheme includes queue management and packet scheduler to transmit class-based packets with different per hop behaviors (PHBs). Simulation results demonstrate effectiveness of the proposed AQC scheme.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.303-308
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• 2004

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.173-182
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• 2005

In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.