• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.396-406
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• 2007

In this paper, we proposed development of improved model reduction and design of hierarchical controller using reduction model. The model reduction is considered that it is the transient response and the steady-state response through the use of nyquist curve. The hierarchical controller selected tuning of PID controller to ensure specified gain and phase margin and hybrid smith-predictor fuzzy controller using reduction model. Simulation examples are given to show the better performance of the proposed method than conventional methods.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1218-1225
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• 2008

This paper presents the design of a neural network based adaptive control for missile is presented. The application model is Exocet MM40, which is derived from missile DATCOM database. Acceleration of missile by tail Fin control cannot be controllable by DMI (Dynamic Model Inversion) directly because it is non-minimum phase system. So, the inner loop consists of DMI and NN (Neural Network) and the outer loop consists of PI controller. In order to satisfy the performances only with PI controller, it is necessary to do some additional process such as gain tuning and scheduling. In this paper, all flight area would be covered by just one PI gains without tuning and scheduling by applying mixture control technique of conventional controller and NN to the outer loop. Also, the simulation model is designed by considering non-minimum phase system and compared the performances to distinguish the validity of control law with conventional PI controller.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.121-126
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• 2002

We proposed the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gains of input-output variables of fuzzy logic controller(FLC) and weights of neural network using Tabu search. Neural network was used for adaptively tuning the output gain of FLC. The weights of neural network was learned from the back propagation algorithm in real-time. To evaluate the usefulness of AFLC, we applied the proposed method to single-machine infinite system. AFLC showed the better control performance than PD controller and GAFLC[8] for. three-phase fault in nominal load which had used when tuning AFLC. To show the robustness of AFLC, we applied the proposed method to disturbances such as three-phase fault in heavy and light load. AFLC showed the better robustness than PD controller and GAFLC[8].

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.8
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• pp.1299-1312
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• 2004

This paper suggests the simple form of a fuzzy PID controller and describes the design principle, tracking performance, stability analysis and changes of parameters of a suggested fuzzy PID controller. A fuzzy PID controller is derived from the design procedure of fuzzy control. It is well known that a fuzzy PID controller has a simple structure of the conventional PID controller but posses its self-tuning control capability and the gains of a fuzzy PID controller become nonlinear functions of the inputs. Nonlinear calculation during fuzzification, defuzzification and the fuzzy inference require more time in computation. To increase the applicability of a fuzzy PID controller to digital computer, a simple form of a fuzzy PID controller is introduced by the backward difference mapping and the analysis of the fuzzy input space. To guarantee the BIBO stability of a suggested fuzzy PID controller, ‘small gain theorem’ which proves the BIBO stability of a fuzzy PI and a fuzzy PD controller is used. After a detailed stability analysis using ‘small gain theorem’, from which a simple and practical method to decide the parameters of a fuzzy PID controller is derived. Through the computer simulations for the linear and nonlinear plants, the performance of a suggested fuzzy PID controller will be assured and the variation of the gains of a fuzzy PID controller will be investigated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.797-803
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• 2012

Proportional solenoid valves are a modulating type that can control the displacement of valves continuously by means of electromagnetic forces proportional to the solenoid coil current. Because the solenoid-type modulating valves have the advantages of fast response and compact design over air-operated or motor-operated valves, they have been gaining acceptance in chemical and power plants to control the flow of fluids such as water, steam, and gas. This paper deals with the auto tuning of the position controller that can provide the proportional and integral gain automatically based on the dynamic system identification. The process characteristics of the solenoid valve are estimated with critical gain and critical period at a stability limit based on implemented relay feedback, and the controller parameters are determined by the classical Ziegler-Nichols design method. The auto-tuning algorithm was verified with experiments, and the effects of the operating point at which the relay control is activated as well as the relay amplitude were investigated.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.504-506
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• 1999

In this paper, we propose a method which control parametric uncertainty systems using PID controller by fuzzy auto tuning. We get the error and the error change rate of plant output correspond to the initial value of parameter using the Ziegler-Nickols tuning and determine the new proportional gain$(K_p)$ and the integral time $(T_i)$ from fuzzy tuner by the error and error change rate of plant output as a membership function of fuzzy theory. The Fuzzy Auto-tuning algorithm for PID controller operate to adapt variable parameter of plant in parametric uncertainty systems. It is shown this method considerably improve the transient response at computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.634-640
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• 2011

When a servo position controller of a robot or a driving units is composed of a PID controller, servomechanism which is modelled is composed of current, velocity and position control loops. After this model is simulated, the technique operating gain of each controller is suggested. The model consists of current, velocity and position controllers from the inside to the outside gradually. Also, to combine velocity and position controllers with 2 order system, simulation is performed after current controllers are composed, which are able for current loop to work ideally. If a current controller is treated with constant, it is possible for velocity and position controller to consist of controller into 2 order system. The technique is verified by applying T-company servo motor which is much more applied to current, velocity and position controller robots.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.1-8
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• 2017

The optimal gain design method of a three-phase boost converter is proposed in this study. The control system has a two-loop configuration, in which each controller is coupled closely; thus, the optimal design is difficult to achieve using conventional gain-tuning method. The proposed method is adopted to the MATLAB SISO TOOL software and is based on the controller requirements, which are phase margin and cut-off frequency of the open-loop system. The optimal proportional -integral gains can be designed easily using the proposed interactive method of the SISO TOOL. The performance of the proposed system is verified through simulation and experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1370-1377
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• 2004

Optimal control gain for time-delay systems is made by an optimal control gain for delay-free systems multiplied by a state transition function for the delay time. The optimal control gain for delay-free systems is obtained by pushing two zeros of the PID controller closely to a larger pole of the second order plant. Thus the optimal tuning of PID controller for time-delay second order system is able to be obtained by calculation for the state transition function.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.173-175
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• 2004

This paper presents a novel design of a self tuning PI controller of induction motor using fuzzy control. In this approach, the fuzzy tuning of a PI controller gains is achieved through fuzzy rules deduced from many robustness simulation tests applied to several induction motors, for a variety of operating conditions such as response to speed command from standstill, step load torque application and speed variations, with nominal parameters and an changed rotor resistance, self inductance and inertia. Simulation results on a speed controller of induction motor are presented to show the effectiveness of the proposed gain 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.