• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.589-594
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• 1989

In this paper, a programming system for robot-based manufacturing cell which can control and simulate manufacturing devices as well as robots in workcell is proposed and developed. The system is based on world model, and modem textual and object-level robot programming language and interactive graphic world modeler are used to construct and exploit world model. Graphic simulation is used as an efficient and easy to use debugging or verifying tool for user written robot programs. Machine dependency is minimized by adopting the hierarchical control structure and by assuming all the workcell components as virtual ones.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.1-12
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• 1999

A design and DSP-based implementation of robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) under the unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the MIT rule. For the disturbances or quickly varying parameters, a quasilinearized and decoupled model which includes the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller which employs Proportional plus Derivative(PD) control. To show the validity of the proposed scheme, simulations and DSP-based experimental works are carried out and compared with the conventional control scheme.

• Journal of Digital Contents Society
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• v.1 no.1
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• pp.23-37
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• 2000

EDI is basically the concept of computer-to-computer exchange of messages relating to various types of activities or business areas, such as banking, trade, medicine, publishing, etc. Therefore, security, reliability and special functionality will be implicit requirements of EDI systems. We will design access control model to content security of these requirements. Access controls in information systems are responsible for ensuring that all direct access to the entities occur exclusively according to the access modes and rules fixed by security policies. On this paper, security policies for access control model are presented from the viewpoints of identity-based, rule-based, role-based policy. We give a design of access control model for secure EDI service based on the derived access control rules and operations to enforce the defined security policies. The proposed access control model provides integrity, confidentiality and a flow control of EDI messages.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.134-140
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• 2017

A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.708-713
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• 1994

A new flux observer based vector control system of an induction motor is constructed by using an observer in which the commanded stator currents are used to estimate the rotor flux. In this system, the flux observer is formulated by using a model of induction motor in a stationary coordinate system. By considering an observer of induction motor in a fixed co-ordinate system located on its secondary flux, a slip frequency controlled type of vector control system is also proposed. From these control schemes, the relation between the conventional slip frequency controlled type system and the observer based one is clarified. The steady-state error of the developed torque which is caused by the parameter change of induction motor is analyzed and discussed for the selection of observer gains. The poles of the observer error dynamics and those of the observer based vector control system are calculated analytically by neglecting the machine parameter change. In order to analyze the robust stability, a linear model of the observer based vector control system is proposed taking into account the machine parameter change. By using this model, the trajectories of the poles and zeros of the torque transfer function are computed and discussed. To test validity of the theoretical analysis, experiments are conducted by using a digital signal processor (TMS320C30) and a current controlled voltage source PWM inverter.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.601-611
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• 2017

This paper proposes a simultaneous control of frequency deviation and electric vehicles (EVs) battery state of charge (SOC) using load frequency control (LFC) and EV controllers. In order to provide both frequency stabilization and SOC schedule near optimal performance within the whole operating regions, a multiple-input multiple-output model predictive control (MIMO-MPC) is employed for the coordination of LFC and EV controllers. The MIMO-MPC is an effective model-based prediction which calculates future control signals by an optimization of quadratic programming based on the plant model, past manipulate, measured disturbance, and control signals. By optimizing the input and output weights of the MIMO-MPC using particle swarm optimization (PSO), the optimal MIMO-MPC for simultaneous control of the LFC and EVs, is able to stabilize the frequency fluctuation and maintain the desired battery SOC at the certain time, effectively. Simulation study in a two-area interconnected power system with wind farms shows the effectiveness of the proposed MIMO-MPC over the proportional integral (PI) controller and the decentralized vehicle to grid control (DVC) controller.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.493-495
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• 2005

This paper proposes a swarm-based fuzzy system modeling technique for coke oven combustion control diagnosis. The coke plant produces coke for the blast furnace plant in steel making process by charging coal into oven and supplying gas to carbonize it. A conventional mathematical model for coke oven combustion control has been used to control the amount of gas input, but it does not work well because of highly nonlinear feature of coke plant. To solve this problem, swarm-based fuzzy system modeling technique is suggested to construct a diagnosis model of coke oven combustion control. Based on the measured input-output data pairs, the fuzzy rules are generated and the parameters are tuned by the PSO(Particle Swarm Optimizer) to increase the accuracy of the fuzzy system is operated. This system computes the proper amount of gas input taking the operation conditions of coke oven into account, and compares the computed result with the supplied gas input.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1683-1693
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• 1997

In this paper, a new nonlinear dynamic model is derived for a 2-dimensional overhead crane based on a new definition of 2-degree-of-freedom swing angle, and a new anti-swing control law is proposed for the crane. The dynamic model and control law take simultaneous travel and traverse motions of the crane into consideration. The model is first linearized for small motions of the crane load about the vertical stable equilibrium. Then the model becomes decoupled and symmetric with respect to the travel and traverse axes of the crane. From this result, a decoupled anti-swing control law is proposed based on the linearized model via the loop shaping and root locus methods. This decoupled method guarantees not only fast damping of load-swing but also zero steady state position error with optimal transient response for the 2-dimensional motion of the crane. Finally, the proposed control method is evaluated by controlling the simultaneous travel and traverse motions of a 2-dimensional prototype overhead crane. The effectiveness of the proposed control method is then proven by the experimental results.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.673-675
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• 1995

A nonlinear process-model based control for main steam temperature control of a 100MW oil-fired drum-type fossil power plant is delveloped and its performances are compared to those of the conventional PID control. The process model for simulation is derived based "first priciple approach" and is validated in steady and transient conditions. The model is in good agreements with the field test data. Performances of the nonlinear PMBC for main steam temperature control are far superior to those of PID in all aspects for the disturbances of ramp increase in load and step change in fuel Btu value.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.148-157
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• 1996

Availability of input trajectories corresponding to desired output trajectories is often important in designing control systems for batch and other transient processes. In this paper, we propose a predictive control-type model-based iterative learning algorithm which is applicable to finding the nominal input trajectories of a linear time-invariant batch process. Unlike the other existing learning control algorithms, the proposed algorithm can be applied to nonsquare systems and has an ability to adjust noise sensitivity as well as convergence rate. A simple model identification technique with which performance of the proposed learning algorithm can be significantly enhanced is also proposed. Performance of the proposed learning algorithm is demonstrated through numerical simulations.