• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.4
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• pp.350-357
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• 2002

Optimal control algorithms for the full storage ice cooling system were developed by using a dynamic simulation program. Control algorithms for the storage charging mode were developed for the chiller outlet temperature setpoint control and the chiller capacity control. Control algorithms for the storage discharging mode were developed for the proper mode selection, the storage-only mode control, and the storage-priority chiller-shared mode control. Two different cases of the expected outdoor air temperature profile and the expected cooling load profile were used to analyze the effectiveness of these algorithms. Simulation results show the energy savings and the satisfactory controls of the ice storage system. Therefore, control algorithms developed for this study may effectively be used for the improved control of the ice storage cooling system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.431-438
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• 2004

This study is on control-gain estimation of energy dissipation control algorithms. Velocity feedback, bang-bang, and energy dissipation control algorithms are proposed based on the Lyapunov stability theory and their performances are evaluated and compared. Saturation problem is considered in the design of the velocity feedback and energy dissipation control algorithms, and chattering problem in bang-bang control is solved by using boundary layer. Numerical results show that the proposed control algorithms can dissipate the structural energy induced by wind loads efficiently, and thus provide good control performance.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.968-971
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• 1996

In this paper, feedback controller is designed for ball-beam system using genetic algorithms. A genetic algorithms are implemented for optimizing gain parameters of feedback controller. We can find optimal point in multi-dimensional search space by using genetic algorithms. Performance of controller is tested by simulation of ball-beam system.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.399-404
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• 2008

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a condensing gas boiler unit, the effective control of the system is necessary. In this study, control algorithms of a condensing gas boiler were developed. Control algorithms are composed of the setpoint algorithm and the control algorithm. The setpoint algorithm consists of the supply water temperature setpoint algorithm and the pump setpoint algorithm. The control algorithm consists of the gas valve control algorithm and the blower control algorithm. In order to analyse the performance of control algorithms, dynamic models of a condensing gas boiler system were used. Simulation results showed that control algorithms developed for this study may be practically applied to the condensing gas boiler.

• Structural Engineering and Mechanics
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• v.75 no.2
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• pp.175-191
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• 2020

In this study, multi-story structures are actively controlled using metaheuristic algorithms. The soil conditions such as dense, normal and soft soil are considered under near-fault ground motions consisting of two types of impulsive motions called directivity effect (fault normal component) and the flint step (fault parallel component). In the active tendon-controlled structure, Proportional-Integral-Derivative (PID) type controller optimized by the proposed algorithms was used to achieve a control signal and to produce a corresponding control force. As the novelty of the study, the parameters of PID controller were determined by different metaheuristic algorithms to find the best one for seismic structures. These algorithms are flower pollination algorithm (FPA), teaching learning based optimization (TLBO) and Jaya Algorithm (JA). Furthermore, since the influence of time delay on the structural responses is an important issue for active control systems, it should be considered in the optimization process and time domain analyses. The proposed method was applied for a 15-story structural model and the feasible results were found by limiting the maximum control force for the near-fault records defined in FEMA P-695. Finally, it was determined that the active control using metaheuristic algorithms optimally reduced the structural responses and can be applied for the buildings with the soil-structure interaction (SSI).

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.676-680
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• 1991

This paper proposes fuzzy control algorithms for a DC moter speed control. The proposed algorithms are constructed by the fuzzy controller and the fuzzy compensator. The fuzzy compensator used to overcome rapidly the effects caused by the disturbance and is mounted outside of the closed loop of the fuzzy controller. The fuzzy control rules are established from human operator experience and basic engineering knowledge about the process dynamics. Simulation results show that the proposed algorithms compensate for parameter variation and disturbance.

• Land and Housing Review
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• v.10 no.3
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• pp.9-16
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• 2019

This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.15-20
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• 2001

In this paper, adaptive algorithms on the sliding model control for robust tracking control of robust manipulators are presented. The presented algorithms use adaption laws for tuning both the sliding mode gain and the thickness of the boundary layer to reject a disconitnuous control input, and to improve the tracking performance. It is shown that the robustness of the developed adaptive algorithms are guaranteed by the sliding mode control law and that the algorithms are globally convergent in the presence of disturbances and modeling uncertainties. Computer simulations are performed for a two-link manipulator, and the results show good properties of the proposed adaptive algorithms under large mainpulator parameter uncertainties and disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1904-1909
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• 1991

Software linear and exponential acceleration/deceleration algorithms for control of machine axes of motion in industrial robots and CNC machine tools are proposed. Typical hardware systems used to accelerate and decelerate axes of motion are mathematically analyzed. Discrete-time state equations are derived from the mathematical analyses for the development of software acceleration/deceleration algorithms. Synchronous control method of multiple axes of motion in industrial robots and CNC machine tools is shown to be easily obtained on the basis of the proposed acceleration/deceleration algorithms. The path error analyses are carried out for the case where the software linear and exponential acceleration/deceleration algorithms are applied to a circular interpolator. A motion control system based on a floating point digital signal processor (DSP) TMS 320C30 is developed in order to implement the proposed algorithms. Experimental results demonstrate that the developed algorithms and the motion control system are available for control of multiple axes and nonlinear motion composed of a combination of lines and circles which industrial robots and CNC machine tools require.

• Journal of KSNVE
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• v.8 no.3
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• pp.485-493
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• 1998

Many of the adaptive noise control systems utilize a form of the least mean square (LMS) algorithms. In the active control of noise, it is common practice to locate an error microphone far from the control source to avoid the near-field effects by evanescent waves. Such a distance between the control source and the error microphone makes a certain level of time-delay inevitable and, hence, may yield undesirable effects on the convergence properties of control algorithms such as filtered-x LMS. This paper discusses the dependence of the convergence rate on the acoustic error path in these popularalgorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. Performances of the new LMS algorithms are presented in comparison with those by the conventional algorithms based on computer simulations and experiments.