• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1888-1893
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• 1991

Systematic design of a controller for a water temperature system was considered, with the intention of devising an accurate control experiment. The results of an experiment using a water temperature system based on the pole placement regulator showed water temperature oscillation and steady state error. This paper proposed a. method for eliminating both the oscillation and the steady state error. The oscillation was eliminated by a drive delay compensation technique, in which a future state value of the system was predicted through a real time computer simulation. The steady state error was eliminated by an steady state error correction technique, in which an actual steady state heatrate in the system model was replaced by an imaginary heatrate. By combining these two techniques, we obtained an experimental result for water temperature control of 0.01 (.deg. C) accuracy. Furthermore, the proposed method was evaluated relatively by comparing the experimental results using several other methods and proved to be the most accurate and convenient control method for the delay system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1371-1376
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• 2003

In the thermal power plant, the main steam temperature is typically regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the 2-DOF PID Controller on the DCS for steam temperature control using immune based multiobjective approach. The stable range of a 2-DOF parameter for only this system could be found for the start-up procedure and this parameter could be used for the tuning problem. Therefore tuning technique of multiobjective based on immune network algorithms in this paper can be used effectively in tuning 2-DOF PID controllers.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.973-978
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• 2009

In this study, the thermal environment characteristics of On-Off control and thermal difference proportional control method in floor radiant heating system were researched by computer simulation. For the analysis of unsteady heat transfer phenomena in household, the method of using electrical equivalent R-C circuit is applied, and radiation heat transfer between panel, ceiling and walls in household is calculated by enclosure analysis method. The parametric study on two control methods, conventional on-off control and temperature error based time control(T.E.B.T.C.) method, are performed to compare thermal heating control performances, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.885-890
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• 2004

Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the Controller with disturbance rejection for thermal power plant using immune based multiobjective approach. An ITSE(Integral of time weighted squared error) is used to decide performance of tuning results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.358-363
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• 2003

Optimal tuning plays an important role in operations or tuning of the complex process such as the main steam temperature of the thermal power plant. However, it is very difficult to maintain the steam temperature of power plant using conventional optimization methods, since these processes have the time delay and the change of the dynamic characteristics in the reheater. Up to the present time, the Pm controller has been used. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper suggests immune algorithm based tuning technique for PID Controller on steam temperature process with long dead time and its results are compared with genetic algorithm based tuning technique.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.482-489
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• 2015

CSTR (Continuous Stirred Tank Reactor) which plays a key role in the chemical plants exhibits highly nonlinear behavior as well as time-varying behavior during operation. The control of CSTRs in the whole operating range has been a challenging problem to control engineers. So, a variety of feedback control forms and their tuning methods have been implemented to guarantee the satisfactory performance. This paper presents a scheme of designing a nonlinear PID controller incorporating with a GA (Genetic Algorithm) for the temperature control of a CSTR. The gains of the NPID controller are composed of easily implementable nonlinear functions based on the error and/or the error rate and its parameters are tuned using a GA by minimizing the ITAE (Integral of Absolute Error). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.525-530
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• 2003

This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature. the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. These parameters tuned by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.154-162
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• 1997

A real time error compensation system was developed to improve the quasistatic volumetric accuracy of a machining center by using sensing, metrology, modeling, and computer control techniques. Including thermal errors, 32 error components are formulated in the time-space domain. Fifteen thermal sensors are used to characterize the temperature field of the machine. A compensation controller based on the IBM/PC has been linked with a CNC controller to compensate for machine errors in real time. The maximum linear displacement error in 4 body diagonals were reduced from 140 ${\mu}m$ to 34.5${\mu}m$ with this compensation system, and the spindle thermal drift in space was reduced from 147.3 ${\mu}m$ to 16.8 ${\mu}m$.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.3
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• pp.200-208
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• 2001

In indoor temperature control of a heat pump, a reduction in energy consumption is very important. However, most control schemes for heat pumps have focused only on control performance such s settling time and steady-state error. In this paper, the model predictive control (MPC) which includes the energy-related variable in this cost function is proposed. By computing the control signal minimizing this cost function, the trade-off between energy reduction and temperature control performance can be obtained. Since the MPC required the process model, the dynamic mode of a heat pump is also obtained by the system identification technique. Performance of the proposed MPC considering energy efficiency is compared with the two other control schemes. It si shown that the proposed scheme can consume less energy thant hte others in achieving similar control performance.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.10
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• pp.381-386
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• 2016

An optimization algorithm is developed based on a simulation case of a single family house model equipped with PV arrays. To increase the nationwide use of PV power generation facilities, a market-competitive electricity price needs to be introduced, which is determined based on the time of use. In this study, quadratic programming optimization was applied to minimize the electricity bill while maintaining the indoor temperature within allowable error bounds. For optimization, it is assumed that the weather and electricity demand are predicted. An EnergyPlus-based house model was approximated by using an equivalent RC circuit model for application as a linear constraint to the optimization. Based on the RC model, model predictive control was applied to the management of the cooling load and electricity for the first week of August. The result shows that more than 25% of electricity consumed for cooling can be saved by allowing excursions of temperature error within an affordable range. In addition, profit can be made by reselling electricity to the main grid energy supplier during peak hours.