• Journal of KSNVE
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• v.8 no.3
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• pp.441-449
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• 1998

A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.97-102
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• 2003

In this paper, a recurrent artificial neural network (RNN) based self-tuning speed controller is proposed for the high-performance drives of induction motors. The RNN provides a nonlinear modeling of a motor drive system and could provide the controller with information regarding the load variation system noise, and parameter variation of the induction motor through the on-line estimated weights of the corresponding RNN. Thus, the proposed self-tuning controller can change the gains of the controller according to system conditions. The gain is composed with the weights of the RNN. For the on-line estimation of the RNN weights, an extended Kalman filter (EKF) algorithm is used. A self-tuning controller is designed that is adequate for the speed control of the induction motor The availability of the proposed controller is verified through MATLAB simulations and is compared with the conventional PI controller.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1577-1586
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• 2017

The Proportional-Integral-Derivative (PID) controller is still the most widespread control strategy in the industry. PID controllers have gained popularity due to their simplicity, better control performance and excellent robustness to uncertainties. This paper presents the optimal tuning of a PID controller for domestic induction heating systems with a series resonant inverter for controlling the induction heating power. The objective is to design a stable and superior control system by tuning the PID controller with a derivative filter (PIDF) through Fuzzy logic. The paper also compares the performance of the Fuzzy PIDF controller with that of a Ziegler-Nichols PID controller and a fine-tuned PID controller with a derivative filter. The system modeling and controllers are simulated in MATLAB/SIMULINK. The results obtained show the effectiveness and superiority of the proposed Fuzzy PID controller with a derivative filter.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.756-762
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• 2006

Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.2
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• pp.336-342
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• 2008

Simple tuning methods of PI, PD and PID controller are proposed for an integrating process with time delay. This is based on matching the coefficients of corresponding powers of s in the numerator and that in the denominator of the closed-loop transfer function. For set-point tracking problem, the derived controller is found to be a PD controller which is shown by Lee's tuning rule based on minimizing the performance indexes (ISE, IAE, ITAE) using a real-coded genetic algorithm. A method can be also proposed PI, PID controllers according to tuning parameter lambda $({\lambda})$ similar to IMC method. Simulation example is given to illustrate the set-point tracking and disturbance rejection performance of the proposed method.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.265-268
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• 1992

The control performances of a fuzzy controller depend on its control rules, I/O membership functions, and scaling factors. Scaling factors are very important to adjust control parameters to the process which is to be controlled. For tuning the sealing factors, trial and error method is used in conventional fuzzy controller, which is very difficult and time consuming. This paper proposes a tuning method of scaling factors based on the concept of tuning rules for the conventional Pl controller parameters. The proposed automatic tuning fuzzy controller was evaluated by computer simulations. Good results have been obtained for the small hydro power plant.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.11
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• pp.1207-1213
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• 2012

Typically commercial controllers do not give data of the controller gains. Therefore, it is very hard to determine the optimal controller gain even though the dynamic model is derived. In this case, design of experiment (DOE) methodology can be a powerful tool for gain tuning. In this research, gain tuning process is proposed based on the DOE. Micro parallel mechanism platform with 3 degrees-of-freedom (DOF) is used for the experiments. Controller gains are measured indirectly from the voltages of adjustable resistors. The controller gains of three actuators are optimized by two or three steps, respectively. The correlations of the controller gains are also analyzed. The process and methodology can be adopted in gain tuning of other mechanical systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.25-28
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• 1995

A Practical application of self-tuning fuzzy controller to a multi-input multi-output complex system of a vehicle engine is investigated. The ovjective is to design a controller to improve the transient performance in torque and RPM mode changes. For the performance improvement in the multivariable comples system, the self-tuning function of internal parameters is essential and practical. The measured output variables using different control schemes are compared the advanteges of the self-tuning fuzzy logic controller are better output performances and the effectiveness in the controller design using many parameters.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.251-253
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• 1993

This paper proposes an automatic tuning fuzzy controller for frequency control of a hydro power plant (HPP). The proposed automatic tuning fuzzy controller consists of fuzzy control part and scaling factor calculation part. Scaling factor tuning is based on the concept of conventional tuning rules for the PI controller. The proposed controller was evaluated by simulation. Good results have been obtained for the 5kW model HHP.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.192-194
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• 1996

This paper propose an optimal scaling gain tuning method of the fuzzy PI controller using Genetic Algorithm(GA). Scaling gains can reflect the control resolution and fuzziness of input/output variables. By the scaling gain method, the design of a fuzzy logic controller(FLC) can be simplified without affecting the system performance in comparison with multi-decision table method. In designing a fuzzy logic controller, the analytic approach method for the optimization is unavailable. Therefore GA is excellent optimization algorithms for scaling gain tuning. Using this optimal scaling gain tuning method, a good performance can be achieved both in transient and steady state.