• Communications for Statistical Applications and Methods
• /
• 제28권4호
• /
• pp.351-368
• /
• 2021

For a probabilistic model with positively skewed data, a lognormal distribution is one of the key distributions that play a critical role. Several lognormal models can be found in various areas, such as medical science, engineering, and finance. In this paper, we propose a new estimator for a lognormal mean and depict the performance of the proposed estimator in terms of the relative mean squared error (RMSE) compared with Shen's estimator (Shen et al., 2006), which is considered the best estimator among the existing methods. The proposed estimator includes a tuning parameter. By finding the optimal value of the tuning parameter, we can improve the average performance of the proposed estimator over the typical range of σ². The bias reduction of the proposed estimator tends to exceed the increased variance, and it results in a smaller RMSE than Shen's estimator. A numerical study reveals that the proposed estimator has performance comparable with Shen's estimator when σ² is small and exhibits a meaningful decrease in the RMSE under moderate and large σ² values.

• 전기학회논문지P
• /
• 제63권4호
• /
• pp.290-294
• /
• 2014

PID(Proportional, Integral, Derivative) controller is the most popular process controllers in nuclear power plants. The optimized parameter setting of the process controller contributes to the stable operation and the efficiency of the operating nuclear power plants. PID parameter setting is tuned when new process control systems are installed or current process control systems are changed. When the nuclear plant is shut down, a lot of PID tuning methods such as the Trial and Error method, Ultimate Oscillation method operation, Ziegler-Nichols method, frequency method are used to tune the PID values. But inadequate PID parameter setting can be the cause of the unstable process of the operating nuclear power plant. Therefore the results of PID parameter setting should be simulated, optimized and finally verified. This paper introduces the simulation method of PID tuning to optimize the PID parameter setting and confirms them of the actual PID controller in the operating nuclear power plants. The simulation method provides the accurate process modeling and optimized PID parameter setting of the multi-loop control process in particular.

• 제어로봇시스템학회논문지
• /
• 제8권12호
• /
• pp.1056-1060
• /
• 2002

Model-based tuning rules of the PID controller are proposed incorporating with real-coded genetic algorithms. The optimal parameter sets of the PID controller for step set-point tracking are obtained based on the first-order time delay model and a real-coded genetic algorithm as an optimization tool. As for assessing the performance of the controllers, performance indices(ISE, IAE and ITAE) are adopted. Then tuning rules are derived using the tuned parameter sets, potential rule models and another real-coded genetic algorithm A set of simulation works is carried out to verify the effectiveness of the proposed rules.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.1371-1376
• /
• 2003

In the thermal power plant, the main steam temperature is typically regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the 2-DOF PID Controller on the DCS for steam temperature control using immune based multiobjective approach. The stable range of a 2-DOF parameter for only this system could be found for the start-up procedure and this parameter could be used for the tuning problem. Therefore tuning technique of multiobjective based on immune network algorithms in this paper can be used effectively in tuning 2-DOF PID controllers.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 B
• /
• pp.504-506
• /
• 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 Advanced Marine Engineering and Technology
• /
• 제30권6호
• /
• pp.753-759
• /
• 2006

Integrating processes are frequently encountered in process industries. In this paper, new tuning formulae of the PID controllers for set-point tracking and load disturbance rejection are presented for integrating processes involving time delay. First, the controller parameter sets are tuned using a real-coded genetic algorithm (RCGA) such that performance criterion(IAE, ISE or ITSE) is minimized. Then, tuning rules are addressed using tuned PID parameter sets. tuning model and another RCGA. The performances of the proposed rules are tested on two processes.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.376-381
• /
• 1992

In this thesis, a self-tuning control method based on Variable Structure System technique for tracking control of Direct-Drive motor is presented. The self-tuning control could not make the tracking error zero in the transient period. This tracking error may be due to disturbances or the error in parameter identification. To overcome this problem, a self-tuning control method based on discrete time VSS technique is presented. The STC based on VSS technique gives good tracking performance of the reference signal in the transient period. The proposed controller is robust to parameter errors and disturbances. The performance of the proposed controller is compared with that of simple STC through digital computer simulation.

• 전기학회논문지
• /
• 제57권9호
• /
• pp.1618-1623
• /
• 2008

In this paper, a new design method for IMC-PID that adds a phase scaling factor of system identifications to the standard IMC-PID controller as a control parameter is proposed. Based on analytically derived frequency properties such as gain and phase margins, this tuning rule is an optimal control method determining the optimum values of controlling factors to minimize the cost function, integral error criterion of the step response in time domain, in the constraints of design parameters to guarantee qualified frequency design specifications. The proposed controller improves existing single-parameter design methods of IMC-PID in the inflexibility problem to be able to consider various design specifications. Its effectiveness is examined by a simulation example, where a comparison of the performances obtained with the proposed tuning rule and with other common tuning rules is shown.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 춘계학술대회 학술발표 논문집
• /
• pp.43-46
• /
• 1998

This paper presents a new parameter tuning method for PID controller. The Ziegler-Nichols Parameter tuning has been widely known as a fairly heuristic method to good determine setting of PID controllers, for a wide range of common industrial processes It has a excessive overshoot in the set point response, set point weighting can reduced the overshoot to specified values. It will also be shown that set point weighting is superior to the conventional solution of reducing large overshoot by other method. In this paper, we will modified the Ziegler-Nichols tuning formula by fuzzy set. These method will give appreciable improvement in the performance of PID controllers.

• Journal of Advanced Marine Engineering and Technology
• /
• 제27권1호
• /
• pp.24-32
• /
• 2003

The PID controller has been widely used in industrial applications due to its simple structure and robustness. Even if it is initially well tuned, the PID controller must be retuned to maintain acceptable performance when there are system parameter changes due to the change of operation conditions. In this paper, a self-tuning control scheme which comprises a parameter estimator, a NN-based rule emulator and a PID controller is proposed, which can cope with changing environments. This method involves combining neural networks and real-coded genetic algorithms(RCGAs) with conventional approaches to provide a stable and satisfactory response. A RCGA-based parameter estimation method is first described to obtain the first-order with time delay model from over-damped high-order systems. Then, a set of optimum PID parameters are calculated based on the estimated model such that they cover the entire spectrum of system operations and an optimum tuning rule is trained with a BP-based neural network. A set of simulation works on systems with time delay are carried out to demonstrate the effectiveness of the proposed method.