• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.279-281
• /
• 2006

In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.51 no.6
• /
• pp.252-257
• /
• 2002

We designed a neuro-fuzzy controller to improve some problems that are happened when the DC servo motor is controlled by a PID controller or a fuzzy logic controller. Our model proposed in this paper has the stable and accurate responses, and shortened settling time. To prove the capability of the neuro-fuzzy controller designed in this paper, the proposed controller is applied to the speed control of DC servo motor. The results showed that the proposed controller did not produce the overshoot, which happens when PID controller is used, and also it did not produce the steady state error when FLC is used. And also, it reduced the settling time about 10%. In addition, we could by aware that our model was only about 60% of the value of current peak of PID controller.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.12
• /
• pp.1903-1910
• /
• 2012

This paper presents a data based low-order controller design algorithm for a linear time-invariant process with a time delay. The algorithm is composed by combining an identification step based on open loop pulse test with a low-order controller design step to obtain the entire set of controllers achieving multiple performance specifications. The initial information necessary for this algorithm are merely the width and amplitude of a rectangular pulse, a controller of four types (PI, PD, PID, first-order), and design objectives. Various parametric approaches that have been developed are merged in the controller design algorithm. The resulting controller set satisfying the design objectives are displayed on the 2D and 3D graphics and thus it is very easy for us to pick a controller inside the admissible set because we can check the corresponding closed-loop performances visually.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.12
• /
• pp.2322-2329
• /
• 2008

In this study, we introduce the design methodology of an optimized fuzzy cascade controller with the aid of particle swarm optimization(PSO) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. We introduce the fuzzy cascade controller scheme which consists of the outer(1st) controller and the inner(2nd) controller as two cascaded fuzzy controllers, and auto-tune the control parameters(scaling facrors) of each fuzzy controller using PSO. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on PSO, is presented in comparison with the conventional PD cascade controller based on serial genetic alogritms.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.5
• /
• pp.225-234
• /
• 2000

In this paper, we present an nonlinear PID controller with network based compensator which consists of a conventional PID controller that controls the linear components and neuro-compensator that controls the output errors and nonlinear components. This controller is based on the Harris's concept where he explained that the adaptive controller consists of the PID control term and the disturbance compensating term. The resulting controller's architecture is also found to be very similar to that of Wang's controller. This controller adds a self-tuning ability to the existing PID controller without replacing it by compensating the output errors through the neuro-compensator. Various simulations and comparative studies have proven that the proposed nonlinear PID controller produces superior results to other existing PID controllers. When applied to an actual magnetic levitation system which is known to be very nonlinear, it has also produced an excellent results.

• Journal of Advanced Marine Engineering and Technology
• /
• v.24 no.4
• /
• pp.502-508
• /
• 2000

The amount of container freight is continuously increasing recently, but freight congestion problem frequently occurs at ports due to low efficiency of container crane in transportation and cargo handling. In this paper, a method for designing a fuzzy controller of the container crane system is presented. In this scheme a mathematical model for the system is obtained in state space representation. The response of the proposed fuzzy controller is compared with that of the optimal controller at the same condition. Through the simulation results, the performance of the fuzzy controller was observed better than that of optimal controller in respect of reference change, disturbances and parameter change. The fuzzy controller was also more stable and robust than the optimal controller.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.54 no.8
• /
• pp.395-401
• /
• 2005

This paper presents Hybrid PI(HBPI) controller of induction motor drive using fuzzy control. In general, PI controllers used in computer numerically controlled machines process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gam tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the KIEE Conference
• /
• 2003.07b
• /
• pp.864-866
• /
• 2003

In this paper, the improvement of control performance for a magnetic levitation system is presented. The model of a single-magnet system with rail is derived. As a conventional controller, PID controller is designed and implemented. This controller has a narrow stability margin due to low-order controller structure so that it cause unstability for a flexible rail. So to improve the control performance and stability margin, a robust controller as a new controller is designed and implemented using a VME-based digital controller. As a result, the controller performance of the new designed controller is better than that of the conventional controller.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.11
• /
• pp.9-15
• /
• 1999

A piezoelectric actuator is widely used in precision positioning applications due to its excellent positioning resolution. However, the piezoelectric actuator lacks in repeatability because of its inherently high hysteresis characteristic between voltage and displacement. In this paper, a controller is proposed to compensate the hysteresis nonlinearity. The controller is composed of a PID and a neural network part in parallel manner. The output of the PID controller is used to teach the neural network controller by the unsupervised learning method. In addition, the PID controller stabilizes the piezoelectric actuator in the beginning of the learning process, when the neural network controller is not learned. However, after the learning process the piezoelectric actuator is mainly controlled by the neural netwok controller. In this paper, the excellent tracking performance of the proposed controller was verified by experiments and was compared with the classical PID controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.726-728
• /
• 2016

In this paper, a realtime MIDI controller is designed using leap motion. The controller makes virtual MIDI port on Windows that it is connected to the port and protocol for communication with DAW or VST. It is converted MIDI data when it is detected a real time the position and shape of hand. This converted data transfer MIDI port by MIDI CC(Control Change). Therefore this controller has the purpose to support flexible MIDI input function than existed MIDI controller.