• Nuclear Engineering and Technology
• /
• v.54 no.6
• /
• pp.2048-2054
• /
• 2022

The coolant temperature feedback coefficient is an important parameter of reactor core power control system. To study the coolant temperature feedback coefficient influence on the core power control system of small PWR, the core power control system is built with the nonlinear model and fuzzy control theory. Then, the uncertainty quantification method of reactor core parameters is established based on the Latin hypercube sampling method and the Bootstrap method. Finally, under the conditions of reactivity step perturbation and coolant inlet temperature step perturbation, uncertainty analysis for two cases is carried out. The result shows that with fuzzy controller and fuzzy PID controller, the uncertainty of the coolant temperature feedback coefficient affects the core power control system, and the maximum uncertainties of core relative power, coolant temperature deviation, fuel temperature deviation and total reactivity are acceptable.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1992.04a
• /
• pp.173-177
• /
• 1992

The Helicopter has a lot of flight modes. The most characteristic flight mode is Hovering. It enables the helicopter to be used in many situations. However, a helicopter has nonlinear dynamics so its mathematical modeling is very difficult. Hence it is not easy to control helicopter in hover. In this paper, RC model helicopter is selected as a plant. To stabilize the behavior of RC model helicopter, Fuzzy alogrithm is used as a controller and one camera is used as a sensor. To get proper Information from camera Image, three characteristic points are attatched to the helicopter and a position recognition algorithm is developed. Experiments are performed to stabilize 3 rotational motions synchronousely with fuzzy control algorithm. As a result, Fuzzy control represents better performances than the conventional PID control.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.7 no.3
• /
• pp.81-88
• /
• 1997

This paper dealt with the position control of a flexible miniature finger driven by piezoelectric bimorph cells, cemented on both side of the finger. Bending moments generated by cells drives the finger, and end-point of the finger is controlled, so as to move in synchrony with fluctation of target and maintain a constant distance between target surface and inger's tip. The voltage applied for the cell is controlled by tip displacement error and error rate. We proposed a PD-Fuzzy controller under conception of PD control strategy. It brought and advantage which reduce number of rules than that of same type conventional fuzzy system and more correct redponse than PID control results.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.852-854
• /
• 1995

This paper proposes a new identification method that utilizes fuzzy inference in parameter identification. The prosed system has an additional control loop where a real plant has replaced by a plant model. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. In this paper, the tuning method which determines parameters of PID controller automatically is described through applying this algorithm to DC servo motor. And we intend to investigate effectiveness of the method by experiments. This method is effective in auto-tuning because the response of the closed loop has verified. The simulated and the experimental results of the dc servo motor are shown to confirm the viability of this method.

• Proceedings of the KIEE Conference
• /
• 2008.04a
• /
• pp.151-152
• /
• 2008

본 논문에서는 도립 역진자 시스템에서의 진자의 도립 상태를 유지하도록 하기 위하여, DSP와 FPGA를 결합하여 ANFIS 뉴로퍼지 제어기를 구현하여 실험하였다. 도립진자의 위치 추종 성능을 PID 제어기와 비교 평가하였다.

• Proceedings of the IEEK Conference
• /
• 2003.07c
• /
• pp.2827-2830
• /
• 2003

Tele manipulator is distingushed from industrial robot by iterating same specified work. Manipulator operator is included in control loop for controlling the telemanipulator because he decide directly during the work and order controllabily reducing the modelling error of telemanipulator which depend on the PID controller. But position-force control method of bidirectional control impose unsafety of vibiration and Analytic Hierachy Method can stabilize for reducing nonlinear modelling error by expert operator because of transformation empirical control rule to linear model.

• Nuclear Engineering and Technology
• /
• v.25 no.2
• /
• pp.222-232
• /
• 1993

In this paper, we present two sets of fuzzy algorithms for the steam generator level control ; one for the high power operations where the flow error is available and the other for the low power operations where the flow error is not available. These are converted to a PID type controller for the high power case and to a quadratic function form of a controller for the low power case. These controllers are implemented on the Compact Nuclear Simulator at Korea Atomic Energy Research Institute and tested by a set of four simulation experiments for each. For both cases, the results show that the total variation of the level error and of the flow error are about 50% of those by the PI controllers with about one half of the control action. For the high power case, this is mainly due to the fact that a combination of two PD type controllers in the velocity algorithm form rather than a combination of two PI type controllers in the position algorithm form is used. For the low power case, the controller is essentially a PID type with a very small integral component where the average values for the derivative component input and for the controller output are used.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.2
• /
• pp.96-101
• /
• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.19 no.1
• /
• pp.80-88
• /
• 2010

In a conventional system, hydraulic unit pumps out pressurized oil when the power use is not even necessary. As a result, it causes much power loss. This study is on the proposal of new hydraulic unit which controls the revolution of the pump in order to produce proper power needed and to have good response characteristic. In addition, the existing control methods such as PID control method, fuzzy control method, and adaptive control method are applied to the proposed hydraulic unit. Then the best control method is selected and the controller is developed to realize minimum power loss.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.374-374
• /
• 2000

In this paper, we developed an ANFIS controller through ES algorithm for disturbances rejection in Hot Rolling. The looper of a Hot Rolling is installed between each pair of stands and plays key roles to enhance the product quality of the strip by controlling the tension and the width of the strip. At the same time, the AGC on top of the Mill produces a strip with the desired thickness through pressing its Mill. Between both, however, interactions are caused by coupling effects among strip tension, looper angle and strip thickness. In addition, in case disturbances, it is more difficult to keep strip quantities desirable. So we present an ANFIS controller through ES algorithm which is able to identify fuzzy rule with input/output data and update itself through output errors.