• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.54-64
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• 1997

In this paper, a method of dynamic modeling and a dynamic control of a mobile robot are presented to show the superiority of the dynamic control comparing to the PD control. This dynamic model is derived from the cartesian coordinates using lagrange equations. Based upon the derived dynamic model, we implemented the dynamic control of the mobile robot using the computed torque method. Time varying non-linear friction terms are not incroporated in this dynamic model. Instead, those are considered as disturbances. This uncertainty in dynamic model of mobile robot is compensated by the outer loop controller using PD algorithm. The validity of this model and the control algorithm are confirmed through the experiments, where the dynamic control algorithm demonstrated robust velocity tracking performance against the unmodeled non-linear frictions. The superiority of this algorithm is demonstrated by comparing to classical PD control algorithm.

• International Journal of Air-Conditioning and Refrigeration
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• v.12 no.3
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• pp.123-130
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• 2004

Control algorithms for an absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. Simulation results showed energy savings and the effective controls of an absorption air conditioning system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.6
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• pp.495-501
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• 2003

Control algorithms for the absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. The simulation results showed energy savings and the effective controls of an absorption air conditioning system.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.58-69
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• 1998

A contrp; suste, fpr SCARA robot is designed for implememting a robust dynamic control algorithm. this study forcuses on the use of DSPs in the design of joint controllers and interfaces in between the host cotroller and four joint controllers and in between the joint controllers and four servo drives. The mechanical body of SCARA robot and the servo drives are selected from the commercially available ones. The four joint controllers, assigned to each joint one by one, are combined into a common system through a mother board hardwarewise and through the global memeory softwarewise. The mother board is designed to connect joint controllers onto the board through the slots adopting PC/104 bus structures. And, the global memory stores the common data which can be shared by joint controllers and the host computer directly, which virtually combines the whole system into one. To demonstrate the performance and efficienty of the sytem, a robust inverse dynamic algorithm is proposed and implemented for a faster and more precise control. The robust inverse dynamic algorithm is basically derived from an inverse dynamci algorithm and a PID compensator. Based upon the derived dynamic equitions of SCARA robot, the inverse dynamic algorithm is intitially implemented within 0.3 msec of the control cycle in this system. The algoithm is found to be not accurate enough for the high speed and precision tasks due to inherent modelling errors and time-varying factors. Therefore, a variable PID algorithm is combined with the inverse dynamic algorithm to support robustness of control performance. Experimental datfor the proposed algorithm are presented and compared with the result obtained from PID and inverse dynamic algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.189-199
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• 1999

This paper presents an optimization algorithm for a stable Self Dynamic Neural Network(SDNN) using genetic algorithm. Optimized SDNN is applied to a problem of controlling nonlinear dynamical systems. SDNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real-time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDW has considerably fewer weights than DNN. Since there is no interlink among the hidden layer. The object of proposed algorithm is that the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed optimized SDNN considering stability is demonstrated by case studies.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.403-410
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• 1999

In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1052-1057
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• 1993

A scara type Direct Drive Arm(DDA) with two degrees-of-freedom is designed and implemented. The direct drive motor is used to furnish large torque to reduce the modeling error by the gear and chains. To control the DDA, a multiprocessor control structure with multirate dynamic control algorithm is designed. In the control algorithm, the dynamics of system is used to calculate the nominal control torque and the feedback controls are calculated with a parallel processing algorithm for each joint. The laboratory experiments on Hong-Ik DDA by dynamic control algorithm are presented and compared to that of PID control algorithm. This result shows that the proposed controller guarantees small trajectory error and stability. With this research, Hong-Ik DDA is expected to be utilized as A basic tool for robotics and control engineering.

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.6
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• pp.196-204
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• 1996

The simplified dynamic models of the timer assembly in the diesel engine fuel injection system were developed. The first order system with time delay was assumed and the various parameters in this model were obtained by experimental data. These simplified dynamic models were used for the development of control algorithm of the injection timing control system. The PI control algorithm was modified to include the anti-windup property and disturbance compensation. This modified PI control algorithm was used for the control of the injection timing. Improved control accuracy and reduced control efforts were observed.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.2
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• pp.147-155
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• 2005

For a long road tunnel, a tunnel ventilation system may be used in order to reduce the pollution level below the required level. To control the tunnel pollution level, a closed loop control algorithm may be used. The cascade control algorithm, which composed of a jet fan control algorithm and an air velocity setpoint algorithm, was developed to regulate the CO level in a tunnel. The verification of control algorithms was carried out by dynamic models developed from real tunnel data sets. The simulation results showed that control algorithms developed for this study were effective to control the tunnel ventilation system.