• Journal of Navigation and Port Research
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• v.35 no.3
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• pp.227-233
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• 2011

This paper presents the tracking and stabilization problem of a night vision system for marine surveillance. Both a hardware system and software modules are developed to control azimuth and elevation axes independently with compensation for ship motion. A two degree of freedom(2DOF) PID controller is designed and its parameters are tuned using a real-coded genetic algorithm(RCGA). Simulation demonstrates the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.101.3-101
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• 2002

Contents 1 Abstract- In the thermal power plant, there are six manipulated variables; main steam flow, feedwater flow, air flow, spray flow, fuel flow, and gas recirculation flow. Therefore, the thermal power plant control system is a multi-input and output system. In the control system, the main steam temperature typically is regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. Up to the present time, the PID controller has been used to operate this system. This paper focuses on the characteristic comparison of the PID controller, the modified 2-DOF PID Controller on the DCS, in order to design an optimal...

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.397-402
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• 1998

PID controller has been used very widely in the industrial applications. But it is difficult tune the PID gains. In this paper, we present a design of optimal 2-DOF PID controller for control of container crane which has to control swing motion and trolley position. For tuning of the 2-DOF PID control gains, we used hybrid evolution program(EP). During operate the crane system in yard, the goal is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high accuracy and rapid transportation is required. However, we developed an optimal controller which has to control the crane system with disturbance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.1
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• pp.78-84
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• 1998

The fluid system such as, the quantity control of raw water, chemicals control in the purification, the waste water system as well as in the feed water or circulation system of the power plant and the ventilation system is controlled with the valve and moter pump. The system's performance and the energy saving of the fluid systems depend on control of method and delicacy. Until, PI controller use in these system but it cannot control delicately because of the coupling in the system loop. In this paper we configure a single flow system to the multi variable system and suggest the application of 2-DOF PID controller and the tuning methods by the neural network to the electrical power of the flow control system. the 2-DOF controller follows to a setpoint has a robustness against the disturbance in the results of simulation. Keywords Title, Intelligent control, Neuro control, Flow control, 2 - DOF control., 2 - DOF control.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.30-37
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• 2000

We studied on acquiring of transfer function and tuning of 2-DOF PID controller using ANFIS for the optimum control to turbine's variables variety. Since the shape of a membership function in the ANFIS based on the characteristics of plant. ANFIS based control method is effective for plant that its variable vary. On the other hand, a start-up time is very short and its variable's value for optimal start-up in gas turbine should be varied, but it is very difficult for such a controller to design. In this paper, we tune 2-DOF PID controller after apply a ANFIS to the operating data of Gun-san gas turbine and verify the characteristics. Its results is compared to the conventional PID controller and discuss. We expect this method will be used for another process because it is studied on the real operating data.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2278-2282
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, a general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, the immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1531-1536
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, A general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, The immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.85-88
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• 2006

Many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is include in the output of a controller. In this paper, the neuro-network 2-DOF PID Controller is designed by a neural network and the gains of this controller are adjusted automatically by the back-propagation algorithm of the neural network when the response characteristic of system is changed under a condition.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.35-41
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• 2006

In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2-DOF PID controller. The experimental results jar an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.781-786
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• 1998

Since a gas turbine is still a significant contributor to peak time, it is very important to tune the gains of P. I. D to get a maximum power and stability within permissible limits. In the gas turbine, the main control loop must adjust the fuel flow to ensure the correct output power and frequency. but it is not easy, because the control loop is composed of many subsystems. In this paper we acquire a transfer function based on the operations data of Gun-san gas turbine and study to apply a loop compensation type 2-DOF PID controller tuning by neural-network to control loop of gas turbine to reduce phenomena caused by integral and derivative actions through simulation. We obtained satisfactory results to disturbances of subcontrol loop such as, fuel flow, air flow, turbine extraction temperature.