• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.5
• /
• pp.703-710
• /
• 1994

This paper describes for the applicability of optimal PID controller to the load frequency control of 2-area power systems. The proposed optimal PID controllers are designed by the optimization technique of P.I.D's gain coefficients using the relatively ingeneous simplex method, and we have considered the system sensitivity for the optimal gains and the stable effects of systems to speed regulation changes. This PID controller for load frequency control systems with exciter shows better performances and robustness than conventional tie-line bias controller.

• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.10 no.1
• /
• pp.1-6
• /
• 2014

PID(Proportional, Integral, Derivative) controller is one of the most used process controllers in nuclear power plants. The optimized parameter setting of process controller contributes to the stable operation and efficiency in the operating nuclear power plants. PID parameter setting is tuned when new process control system is established or process control system is changed. It is a burdensome work for I&C(Instrument and Control) engineers to tune the PID controller because it requires a lot of experience and knowledge. When the plant is in operation, inadequate PID parameter setting can be the cause of the unstable process of the plant. Therefore the results of PID parameter setting should be compared, simulated, verified and finally optimized. The practical PID tuning methods used in process controller are tuning operation calculation(Ziegler-Nicholes, Minimum TIAE, Lambda, IMC), exclusive tuning program based on computer and Matlab application. This paper introduces the various tuning methods and suggests an optimized PID tuning process in the operating nuclear power plants.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.1 no.1
• /
• pp.95-103
• /
• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.1
• /
• pp.88-95
• /
• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.3
• /
• pp.536-544
• /
• 2011

In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.12
• /
• pp.1137-1147
• /
• 2004

In this paper, we proposed two types of adaptive control mechanism which is named HIA(Humoral Immune Algorithm) PID and CMIA(Cell-Mediated Immune Algorithm) controller based on biological immune system under engineering point of view. The HIA PID which has real time control scheme is focused on the humoral immunity and the latter which has the self-tuning mechanism is focused on the T-cell regulated immune response. To verify the performance of the proposed controller, some experiments for the control of AGV which is used for the port automation to carry container without human are performed. The experimental results for the control of steering and speed of an AGV system illustrate the effectiveness of the proposed control scheme. Moreover, in that results, proposed controllers have better performance than other conventional PID controller and intelligent control method which is the NN(neural network) PID controller.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.4
• /
• pp.259-269
• /
• 2003

This paper considers the problem of determining a set of PI, PD and PID controller gains, for a given linear time invariant plant, that meets or exceeds the closed loop step response specifications. The proposed method utilizes two recent results: for a given system, (1) finding a set of stabilizing PI, PD and PID gains and (2) the relationship between time response (overshoot and speed) and the coefficients of the characteristic polynomial. The method allows us to extract a subset of PI, PD and PID gains that meets stability as well as time domain performance requirements. The intersections of two dimensional sets described by linear and quadratic inequalities in the controller design space are need to be Identified through numerical computation. The procedure is illustrated by examples.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.12
• /
• 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.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.7
• /
• pp.66-77
• /
• 1997

This paper presents an automatic tuning method for parameters of a multivaiable self-tuning velocity-type PID controller which adapts to changes in the system parameters with time delays and noises. The velocity-type PID control structure is determined in the process of minimizing the variance of the auxiliarly output, and self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optiminzing the design parameters of the controller. The proposed PID type multivariable self-tuning method is simple andeffective compared with other esisting multivariable self-tuning methods. Computer simulation has shown that the proposed algorithm is beter than the trial-and-error method in the tracking performance.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.5
• /
• pp.724-729
• /
• 2012

A fuzzy PID controller design method is proposed for precise robust control of DC-DC buck converters. The PID parameters are determined reflecting on the common control engineering knowledge that transient performances can be improved if the P and I gains are big and the D gain is small at the beginning. Different from the previous fuzzy control design methods, the proposed method requires no defuzzification module and the global stability of the proposed fuzzy control system can be guaranteed. The proposed fuzzy PID controller is implemented by using a low-cost 8-bit microcontroller, and simulation and experimental results are given to demonstrate the effectiveness of the proposed method.