• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.40-46
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• 1999

A self-tuning FPID(Fuzzy Proportional Intergral Derivative) controller fo load frequency control of 2-area power systemis proposed in this paper. The paramters of the proposed self-tuning FPID controller are self-tuned by the proposed fuzzy inference technique. Therefore in this paper the fuzzy inference technique of PID gains using PSGM(Product Sum Gravity Method) is presented and is applied to the load frequency control of 2-area power system. The computer simulation results show that the proposed controller give better more control characteristics than convention-al PID, FLC under load changes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.4
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• pp.184-192
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• 1985

The parameter regulation of proportional-plus-intergral-plus-derivative output feedback controllers is presented in the practical compter simulation and the time-domain analysis. Particularly, the restriction of parameter regulation for PID controller utilization is investigated as a result of simulation method. It is finally noted that one may resort to the design of controllers, as investigated, for rapid steady-state response, disturbance rejection, and transient response performance (over 3rd-order process) without computing the open-loop transfer functionmatrix. in consequence is presented the block diagram of sensor base system for PID output feedback controllers.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.299-303
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• 1993

There can be two methods in control systems: one is to use a linear controller, the other is to use a nonlinear controller. The PID controller and the fuzzy controller can be said to belong the linear and the nonlinear controller respectively. In this paper, a new hybrid controller which is consist of the linear PID controller of which the gain is tuned and the nonlinear self tuning fuzzy controller is proposed. In the PID controller, an algorithm which parameterizes the proportional, the intergral, and the derivative gain as a single parameter is used to improve the performance of the PID controller. In the self tuning fuzzy controller, an algorithm which changes the shape of the triangle membership function and changes the scaling factor which is multiplied to the error and the error change. The evaluation of the performance of the suggested algorithm is carried on by the simulation for the Rhino XH-2 robot manipulator with 5 links revolute joints.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.2
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• pp.53-62
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• 2018

This study propose a new approach to control the optimal working path of vertical type articulated robot with translation joint for trimming working process automation in forging manufacturing process. The basic structure of the proposed robotic joints controller consists of a Proportional-Intergral controller and a Proportional-Derivative controller in parallel. The proposed control scheme takes advantage of the properties of the fuzzy PID controllers. The proposed method is suitable to control of the trajectory and path control in cartesian space for vertical type articulated robot manipulator. The results illustrates that the proposed fuzzy computed torque controller is more stable and robust than the conventional computed torque controller. The reliability is varified by simulation test for vertical type s articulated robot with seven joints including one trqanslation joint.