• 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.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.51-55
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• 2005

Assuring integrity of permission assignment (PA) constraints is a difficult task in role-based access control (RBAC) because of the large number of constraints, users, roles and permissions in a large enterprise environment. We provide solutions for this problem using the conflict concept. This paper introduces the conflict model in order to understand the conflicts easily and to detect conflicts effectively. The conflict model is classified as a permission-permission model and a role-permission model. This paper defines two type conflicts using the conflict model. The first type is an inter-PA-constraints (IPAC) conflict that takes place between PA constraints. The other type is a PA-PAC conflict that takes place between a PA and a PA constraint (PAC) Also, the conditions of conflict occurrence are formally specified and proved. We can assure integrity on permission assignment by checking conflicts before PA and PA constraints are applied.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.50.3-50
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• 2001

Nonlinear feedback control scheme for reactive distillation column has been proposed. The proposed control scheme is derived in the framework of Nonlinear Internal Model Control. The product compositions and liquid and vapor flow rates in sections of the reactive distillation column are estimated from selected tray temperature measurements by an observer. The control scheme is applied to example reactive distillation column in which two products are produced in a single column and the reversible reaction A + B = C + D occurs. The relative volatilities are favorable for reactive distillation so that the reactants are intermediated boilers between the light product C and the heavy product D. Ideal physical properties, kinetics and ...

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.415-425
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• 2000

An open architecture manufacturing strategy intends to integrate manufacturing components on a single platform so that a particular component can be easily added and/or replaced. Therefore, the control scheme based upon the open architecture concept is hardware-independent. In this paper, a modular and object oriented approach for a PC-based open robot control system is investigated. A standard reference model for robot systems, which consists of three modules; hardware module, operating system module, and application software module, is first proposed. Then, a PC-based Open Robot Controller(PC-ORC), which can reconfigure robot control systems in various production environments, is developed. The PC-ORC is built upon the object-oriented method, and allows an easy implementation and modification of various modules. The PC-ORC consists of basic softwares, application objects, and additional hardware device on the PC Platform. The application objects are: sequencer, computation unit, servo control, ancillary equipment, external sensor control, and so on. In order to demonstrate the applicability of the PC-ORC, the proposed PC-ORC configuration is applied to an industrial SCARA robot system.

• Journal of Power Electronics
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• v.7 no.2
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• pp.159-173
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• 2007

In this paper, an intelligent sliding-mode position controller (ISMC) for achieving favorable decoupling control and high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent position controller consists of a sliding-mode position controller (SMC) in the position feed-back loop in addition to an on-line trained fuzzy-neural-network model-following controller (FNNMFC) in the feedforward loop. The intelligent position controller combines the merits of the SMC with robust characteristics and the FNNMFC with on-line learning ability for periodic command tracking of a PMSM servo drive. The theoretical analyses of the sliding-mode position controller are described with a second order switching surface (PID) which is insensitive to parameter uncertainties and external load disturbances. To realize high dynamic performance in disturbance rejection and tracking characteristics, an on-line trained FNNMFC is proposed. The connective weights and membership functions of the FNNMFC are trained on-line according to the model-following error between the outputs of the reference model and the PMSM servo drive system. The FNNMFC generates an adaptive control signal which is added to the SMC output to attain robust model-following characteristics under different operating conditions regardless of parameter uncertainties and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode position controller. The results confirm that the proposed ISMC grants robust performance and precise response to the reference model regardless of load disturbances and PMSM parameter uncertainties.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.304-311
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• 2012

So far, the importance for an accurate load model has been constantly raised and its necessity would be further more emphasized. Currently used load model for analysis of power system in Korea was developed 10 years ago, which is aggregated by applying the statistically estimated load compositions to load models based on individual appliances. As modern appliances have diversified and rapidly changed, the existing load model is no longer compatible with current loads in the Korean power system. Therefore, a measurement based load model is more suitable for modern power system analysis because it can accurately include the load characteristics by directly measuring target load. This paper proposes a ZIP model employing a Kalman-filter as the estimation algorithm for the model parameters. The Kamlan-filter based parameter identification offers an advantage of fast parameter determination by removing iterative calculation. To verify the proposed load model, the four-second-interval real data from the Korea Energy Management System (K-EMS) is used.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.933-935
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• 1999

In this paper, we present model predictive control scheme based on neural network to control discrete-time chaotic systems. We use a feedforward neural network as nonlinear prediction model. The training algorithm used is an adaptive backpropagation algorithm that tunes the connection weights. And control signal is obtained by using gradient descent (GD), some kind of LMS method. We identify that the system identification results through model prediction control have a great effect on control performance. Finally, simulation results show that the proposed control algorithm performs much better than the conventional controller.

• Journal of Drive and Control
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• v.15 no.3
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• pp.1-7
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• 2018

Humanoid robots have fascinated many researchers since they appeared decades ago. For the requirement of both accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Humanoid robots are highly nonlinear, coupled, complex systems, accordingly the calculation of robot model is difficult and even impossible if precise model of the humanoid robots are unknown. Therefore, it is difficult to control using traditional model-based techniques. To realize model-free torque control, time-delay control (TDC) for humanoid robot was proposed with time-delay estimation technique. Using optimal walking trajectory obtained by particle swarm optimization, TDC with proposed scheme is implemented on whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the proposed TDC for humanoid robots.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1510-1515
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• 2005

This paper is concerned with a Logic-based Fuzzy Neural Networks (LFNN) with the aid of fuzzy granulation. As the underlying design tool guiding the development of the proposed LFNN, we concentrate on the context-based fuzzy clustering which builds information granules in the form of linguistic contexts as well as OR fuzzy neuron which is logic-driven processing unit realizing the composition operations of T-norm and S-norm. The design process comprises several main phases such as (a) defining context fuzzy sets in the output space, (b) completing context-based fuzzy clustering in each context, (c) aggregating OR fuzzy neuron into linguistic models, and (c) optimizing connections linking information granules and fuzzy neurons in the input and output spaces. The experimental examples are tested through two-dimensional nonlinear function. The obtained results reveal that the proposed model yields better performance in comparison with conventional linguistic model and other approaches.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1123-1130
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• 2017

This paper deals with the dynamic surface control based tracking control for a drone equipped with a 2-DOF manipulator. First, the dynamics of drone and 2-DOF manipulator are derived separately. And we obtain the combined model of a drone equipped with a manipulator considering the inertia and the reactive torque generated by a manipulator. Second, a dynamic surface control based attitude and altitude control method is presented. Also, multiple sliding mode control based position control method is presented. The system stability and convergence of tracking errors are proven using Lyapunov stability theory. Finally, the simulation results are given to verify the effectiveness of the proposed control method.