• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1101-1105
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• 2012

This study proposes a method for improvement of PD type fuzzy controller. The method includes self tuner using gradient algorithm that is one of the optimization algorithms. The proposed controller improves simple Takagi-Sugeno type FLC (Fuzzy Logic Control) system. The simple Takagi-Sugeno type FLC system changes nonlinear characteristic to linear parameters of consequent membership function. The simple FLC system could control the system by calibrating parameter of consequent membership function that changes the system response. While the determination on parameter of the simple FLC system works well only partially, the proposed method is needed to determine parameters that work for overall response. The simple FLC system doesn't predict the response characteristics. While the simple FLC system works just like proportional part of PID, our system includes derivative part to predict the next response. The proposed controller is constructed with P part and D part FLC system that characteristic parameter on system response is changed by self tuner for effective response. Since the proposed controller doesn't include integral part, it can't eliminate steady state error. So we include a gain to eliminate the steady state error.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.482-489
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• 2015

CSTR (Continuous Stirred Tank Reactor) which plays a key role in the chemical plants exhibits highly nonlinear behavior as well as time-varying behavior during operation. The control of CSTRs in the whole operating range has been a challenging problem to control engineers. So, a variety of feedback control forms and their tuning methods have been implemented to guarantee the satisfactory performance. This paper presents a scheme of designing a nonlinear PID controller incorporating with a GA (Genetic Algorithm) for the temperature control of a CSTR. The gains of the NPID controller are composed of easily implementable nonlinear functions based on the error and/or the error rate and its parameters are tuned using a GA by minimizing the ITAE (Integral of Absolute Error). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of the proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.593-608
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• 1995

In this study two issues are considered, one is to develop a pneumatic servomechanism using a direct-connected circuit between inlet and outlet, the other is to design two kinds of advanced controllers such as fuzzy and PID controllers for a fingering system. Besides, the application of the advanced controllers to the newly proposed servomechanism is presented. The procedure of this study is composed of following 6 steps : [Step 1] Structuring of a control system; [Step 2] Development of a pneumatic circuit for the servomechanism ; [Step 3] Characteristic analysis of the valve and cylinder systems ; [Step 4] Determination of optimal parameters of the PID controller ; [Step 5] Design of a fuzzy controller and parameter tuning; and, [Step 6] Experimental analysis of fuzzy and PID controllers. Experimental results show that the newly proposed pneumatic servomechanism has good performance and, not only the performance of the fuzzy controller is better than that of the PID controller but also the fuzzy controller fits well to the control of the pneumatic servomechanism.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.2
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• pp.195-205
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• 1997

The propulsion marine diesel engine have been widely applied with a mechanical- hydraulic governor to control the ship speed for long time. But it was recently very difficult for the mechani¬cal - hydraulic governor to control the speed of engine under the condition of low speed and low load because of jiggling by rough fluctuation of rotating torque and hunting by dead time of Desiel engnie The performance improvement of mechanical - hydraulic governor is required to solve these problems of control system. The electro - hydraulic governor using PID algorithm is provided to compensate the faults of mechanical- hydraulic governor. In this paper, in order to analyze the ship speed control system, the transfer function was converted from the z tansformation to w transformation. The influence of dead time changing by engine speed which induces hunting phenomena was investigated by Nichols chart of w plane. As a method of performance improvement of mechanical hydraulic governor, a Eletro - hydraulic governor shows that fine control results can be obtained through optimal parameter tuning of PID

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.369-369
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• 2000

Control system by means of fuzzy theory has demonstrated its robustness in applying to the high-order and nonlinear dynamic system in that it can utilizes the human expert knowledges in system design. In this paper, first, the design methodology of HFC combined PID controller with fuzzy controller by membership function of weighting coefficient is proposed. Second, Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to improve the performance of hybrid fuzzy controller. Especially, in order to obtain the optimal scaling factors and PID parameters of HFC using GA based on advanced initial individual, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed in ITAE, overshoot and rising time to show applicability and superiority with simulation results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.11
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• pp.619-625
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• 2003

We proposed an optimum PID controller design method of the Smith Predictor It can be applied to various processes. The real process is approximated via the second order plus time delay model (SOPTD) whose parameters are specified through a model reduction algorithm. We already proposed a new model reduction method that considered four point in the Nyquist curve to reduced the steady state error between the real process model and the reduced model using the gradient decent method and the genetic algorithms. In addition, the Smith predictor is used to compensate time delay of the real process model. In this paper, the new optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.77-82
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• 2010

An analytical method for robust design of the multi-loop proportional-integral (PI) controller is proposed for various types of multi-delay processes. On the basis of the direct synthesis and generalized IMC-PID approach, the analytical tuning rules of the multi-loop PI controller are firstly derived for achieving the desired closed-loop response, and the structured singular value synthesis is then utilized for the tradeoffs between the robust stability and performance by adjusting only one design parameter (i.e., the closed-loop time constant). To verify the superiority of the proposed method, the simulation studies have been conducted on a wide variety of multivariable processes. The multi-loop PI controller designed by the proposed method shows a fast, well-balanced and robust response with the minimum integral absolute error (IAE) in compared with other renowned methods.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.999-1001
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• 1995

In this study, the algorithm of optimal parameter inference is proposed. At this inferring method, we tried to acquire the follow-up to reference pattern through comparing the plant output pattern with random reference pattern. As an inference method, the fuzzy theory was applied and the proposed algorithm was proved by computer simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.2
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• pp.219-225
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• 2002

Parameter tuning methods by Ziegler-Nichols for PID controllers are generally classified into Z-N(1) and Z-N(2). The purpose of this paper is to describe what relations exist between the methods of Z-N(1) and Z-N(2), or how Z-N(1) can be originated from Z-N(2) by analyzing one loop control system composing of P or PI controller and time delay process. In this paper, for the first step to seek mutual relations, the simple formulas of Z-N(2) are transformed into those composing of the same parameters as Z-N(1) which is derived from the analysis of frequency characteristics. Then, the approximation of the actual ultimate frequency is proposed as important premise in the translation between Z-N(1) and (2). Such equalization and approximation brings a simple approximated formula which can explain how Z-N(1) is originated from the Z-N(2) in the form of formula.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.874-881
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• 2010

A automatic flight control system(AFCS) of UAS needs to control its flight path along target path exactly as adjusts flight coefficient itself depending on static or dynamic changes of airplane's features such as type, size or weight. In this paper, we propose system which tunes control gain autonomously depending on change of airplane's feature in flight as adding MLM(Machine Learning Module) on AFCS. MLM is designed with Linear Regression algorithm and Reinforcement Learning and it includes EvM(Evaluation Module) which evaluates learned control gain from MLM and verified system. This system is tested on beaver FDC simulator and we present its analysed result.