• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.815-817
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• 1999

In the two-mass system driving a load through a flexible shaft or transmission system, a shaft torsional vibration is often generated. In this case, it's difficult to control only by conventional PI controller. To solve this problem. the two-mass speed control system with PID controller is designed by using pole assignment method, and an optimum PID parameters are derived by evaluating ITAE(Integral of time multiplied by the absolute error) performance index. Simulation results show the validity of the proposed PID controller and this controller is compared with the conventional PID controller.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.5
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• pp.785-790
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• 2008

A technique for determining the feedback gain of the states feedback controller using a real-coded genetic algorithm(RCGA) is presented. It is concerned with the states error to the performance index of a RCGA. As for assessing the performance of the controller three performance criteria (ISE. IAE and ITAE) are adopted. And designing the controller involves a constrained optimization problem. Therefore a real-coded genetic algorithm incorporating the penalty strategy is used. The performance of the proposed method is demonstrated through a set of simulation about an inverted pendulum system.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.721-728
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• 2009

PID control is widely used to control stable processes, however, PID control for unstable processes is less common. In this paper, systematic tuning methods are derived to tune the PID controller for unstable FOPTD(Forst Order Plus Time Delay) processes. The proposed PID controllers for set-point tracking and disturbance rejection problem are tuned based on minimizing the performance indexes (IAE, ISE, ITAE) using a real-coded genetic algorithm. Simulation example is given to illustrate the set-point tracking and disturbance rejection performance of the proposed method.

• 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.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2545-2547
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• 2000

In this paper, a hybrid fuzzy controller using genetic algorithm based on parameter estimation mode to obtain optimal control parameter is presented. First, The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PID's output in steady state by a fuzzy variable, namely, membership function of weighting coefficient. Second, genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller utilizing the conventional methods for finding PID parameters and estimation mode of scaling factor. The algorithms estimates automatically the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules according to the rate of change and limitation condition of control input. Computer simulations are conducted to evaluate the performance of proposed hybrid fuzzy controller. ITAE, overshoot and rising time are used as a performance index of controller.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1447-1453
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• 2008

In this paper, we proposed to improve performance of the design of a cascade controller with the smith-predictor structure. The parameters of controller in the inner loop are determined to minimize the integral of time multiplied by the absolute value of error (ITAE) value of performance Index. The controller of outer loop and parameters of Smith-Predictor can be obtain 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. Simulation examples are given to show the better performance of the proposed method than conventional methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.6
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• pp.633-641
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• 2015

Several complex processes that are employed in industries, such as shipping, power plants, and the petrochemical industry, involve time-varying behavior as well as strong nonlinear behavior during operation. The fixed-parameter proportional-integral-derivative (PID) controllers have difficulty in dealing with control problems that occur in such processes. In this paper, we propose a method of designing a nonlinear PID controller for industrial processes that exhibit a large number of nonlinearities and time-varying behavior. The gains of the nonlinear PID controller are characterized by a simple nonlinear function of the error and/or error rate depending on the process set-point and output. We tune the user-defined parameters using a genetic algorithm by minimizing the integral of time absolute error (ITAE) index. We verify the effectiveness of the proposed method by performing a comparison of the proposed method and two other nonlinear and adaptive methods that are employed for reference tracking, disturbance-rejection performances, and robustness to parameter changes on a continuously stirred tank reactor.