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

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.873-883
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• 2008

This paper presents a parametric study on the controller design scheme for a gyro-accelerometer to have robust performance under some parameter variations. In particular, an integral and derivative based controller design method is suggested to achieve the desired performances of stability margin, bandwidth, and uniformity of scale for both gyroscopes and accelerometers with uncertainties of quality factor and resonant frequency. The simulation result shows that the control loop based on the suggested method gives satisfactory performance robustness under parameter variations, demonstrating the usefulness of the proposed design scheme.

• Transactions of The Korea Fluid Power Systems Society
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• v.3 no.2
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• pp.14-20
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• 2006

A controller design procedure for an electro-hydraulic positioning systems has been developed using $H{\infty}$ control. The generalized plant models and weighting function for multiplicative uncertainty modelling error was presented along with $H{\infty}$ controller designs in order to investigate the robust stability and performance. Both disturbance rejection and command tracking performances were improved with the $H{\infty}$ controller, and the better uniformity of time response is achieved across wide range of operating conditions than the PID, LQR and LQG control scheme. The multiplicative uncertainty case was specifically suited for the design of an electro-hydraulic positioning control systems using $H{\infty}$ control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1207-1210
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• 2003

In this paper, studied traveling by ummaned vehicles using MPC sensor.Explain what is MPC sensor and also is threaded how on vehicles. Made use of PID controller and LQG/LTR controller that is used much in present industrial circles for control of this.

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

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.397-400
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• 1991

This paper presents a cartesian space decentralized adaptive controller design for the end effector of the robot manipulator to track the given desired trajectory in the cartesian coordinate. By the cartesian based control scheme, the task related high level motion command is directly executed without solving the complex inverse kinematic equations. The controller does not require the complex manipulator dynamic model, and hence it is computationally very efficient. Each degree of freedom of the end effector on the cartesian space is controlled by a PID feedback controller and a velocity acceleration feed forward conpensation part. Simulation results for a two-link direct drive manipulator conform that the present cartesian based decentralized scheme is feasible.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.346-349
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• 2003

For a traveling crane, various control methods such as neural network predictive control and TDOFPID(Two Degree of Freedom Proportional Integral Derivative) are studied. So in this paper, we proposed improved navigation method to reduce transfer time and sway with anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the NNPPID(Neural Network Predictive PID) controller to control the precise move and speedy navigation. The proposed predictive control system is composed of the neural network predictor, TDOFPID controller, and neural network self-tuner. We analyzed ASC(Automated Stacking Crane) system and showed some computer simulations to prove excellence of the proposed controller than other conventional controllers.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.30 no.4
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• pp.320-328
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• 1994

In 1980 s to 1990 s the marine propulsion diesel engines have been developed into lower speed and longer stroke for the enegy saving (small S.F.O.C). As these new trends the conventional mechanical-hydraulic governors were not adapted to the new requirements and the digital governors have been adopted in the marine use. The digital governors usually use the control algorithms such as the PID control, optimal control, adaptive control and etc. While the engine has delay time and parameter variations these control algorithms have difficulty in considering the stability and the robustness for the model uncertainty. In this study, the $H_{\infty}$ controller design method are applied in order to design the feedback controller K(s) to the speed control of the low speed marine diesel engine, and the two-degree-of-freedom control system is constituted with $H_{\infty}$controller. By comparison of responses of the two-degree-of-freedom control system under the delay time and parameter variations is confirmed.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.65-74
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• 2002

This paper examines the usefulness of a Brake Steer System (BSS), which uses differential brake forces for steering intervention in the context of Intelligent Transportation Systems (ITS). In order to help the car to turn, a yaw moment can be achieved by altering the left/right and front/rear brake distribution. This resulting yaw moment on the vehicle affects lateral position thereby providing a limited steering function. The steering function achieved through BSS can then be used to control lateral position in an unintended road departure system. A 8-DOF nonlinear vehicle model including STI tire model will be validated using the equations of motion of the vehicle. Then a controller will be developed. This controller, which will be a PID controller tuned by Ziegler-Nichols, will be designed to explore BSS feasibility by modifying the brake distribution through the control of the yaw rate of the vehicle.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.281-287
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• 2002

This paper investigates on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several inde-pendent, but interacting processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause and effect of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controller's performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice far NCS due to its robustness against parameter uncertainty.