• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.167-169
• /
• 2005

This paper proposes an optimum tuning which improves the tuning effect of IMC-PID and guarantees the performance and robustness of controller system by considering gain margin, phase margin, sensitivity functions and integral square error(ISE) for IMC-PID controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.465-468
• /
• 1998

In this paper, merits of both fuzzy and PID controllers are combined. The combined controller is designed such that the tuning of the PID controller is achieved by the basic fuzzy controller via its rule base. The proposed scheme avoids the tuning of PID parameters which is always a time consuming task, difficult to carry out and often poorly done. Computer simulations are made to demonstrate the satisfactory tracking performance of the combined fuzzy-PID controller.

• Journal of Advanced Marine Engineering and Technology
• /
• v.29 no.1
• /
• pp.116-123
• /
• 2005

The PID controllers have been widely accepted in many industrial systems due to their robust performance in a wide range of operating conditions and their functional simplicity To implement a PID controller, its three parameters must be determined for the given plant. Conventional tuning methods are mainly based on experience and experiment and are lack of systematic procedure Recently. to overcome drawbacks of conventional tuning methods, genetic algorithms have been used, In this paper a real-coded genetic algorithm is employed to search for the optimal parameters of the PID controller for speed control of marine gas turbine engines. Simulation results show the effectiveness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.102.5-102
• /
• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied by immune algorithm for a process. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Simulation results by immune based tuning reveal that tuning approaches suggested in this paper is an effective approach to search for optimal or near optimal process control.

• Proceedings of the KIEE Conference
• /
• 2001.07b
• /
• pp.1182-1184
• /
• 2001

This paper presents a neural network based self-tuning fuzzy PID control scheme for induction motor speed control. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PID controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.5
• /
• pp.830-836
• /
• 2006

In this paper described an auto tuning neuro-fuzzy PID controller based neural network. The PID type controller has been widely used in industrial application due to its simply control structure, easy of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. In this paper will design to take advantage of neural network fuzzy theory and pid controller auto toning technique. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. This controller simple structure and computational complexity are less, and also application is easy and performance is excellent in system that is strong and has nonlinearity to system dynamic behaviour change or disturbance. Finally, the proposed auto tuning neuro-fuzzy controller is applied to magnetic levitation. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• Journal of Satellite, Information and Communications
• /
• v.11 no.4
• /
• pp.39-43
• /
• 2016

In this paper, we propose PID gain auto tuning method in steering type mobile robot. PID controller gain select method are various methods. Ziegler-Nichols step tuning method is one method tuning in PID controller. Use step tuning method find a the first gain and did experiment in steering mobile robot. and Make a new the second gains from the first gains. After appling the second gain in PID controller, Where perform observe for convergence time and stabilization error. Experiments result the second gain are useful in real steering mobile robot system.

• Journal of Convergence Society for SMB
• /
• v.4 no.1
• /
• pp.31-39
• /
• 2014

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedback were changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control. We also applied to reference tracking problem with the designed auto-tuning scheme.

• Journal of the Korea Convergence Society
• /
• v.4 no.4
• /
• pp.31-40
• /
• 2013

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedbackwere changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.10
• /
• pp.1251-1258
• /
• 1999

The water level control of a steam generator in the unclear power plant is an important process. Most of the water level controllers of the actual plant are PID controllers. But they have limitations in appling for tracking the set point and getting rid of disturbances, so there are some defects to apply in the actual ground even though many research works represented the resolutions to solve it. In this paper, it is suggested that the established simple PID controller in low power has the ability to remove disturbances and trace the set-point, and then possesses the real-time self-tuning function according to the variety of moving peculiarity of a plant. This function realized by making use of fuzzy logic. PID parameters are formulated by a variable ${\alpha}$ and made it fluctuate by a fuzzy inference according to level error and level error change. This mechanism makes application of actual plant effective as well as taking advantage of improving the efficiency of water level controller by way of adding the function of self-tuning instead of replacing PID controller. The computer simulation of this scheme shows the improved performance compare to conventional PID controller.