• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1496-1499
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• 2005

In this paper, we applied step motor drive using a fuzzy logic control based on PID controller. A designed this controller's purpose is improved robust and autonomous characteristic in which the variation of external load affects plant parameter. Therefore, in this paper, using a fuzzy logic control based on PID controller of two fuzzy-PI and fuzzy-D is obtained decremental overshoot and a special response quality.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.1
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• pp.136-144
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• 2004

In general a hydraulic system which uses a single rod hydraulic as an actuator is modeled as a nonlinear system and reveals uncertain Parameter characteristics such as the density variation of hydraulic oil and is subject to load variations and severe disturbances during operation. A variable design-parameter fuzzy PID controller is adopted to solve these undesirable internal and external problems and its effectiveness is verified through computer simulations for control performance and real time control possibility.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.1
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• pp.1-10
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• 2003

This paper is concerned with the fuzzy control scheme and PID controller for the vibration suppression control of a cantilever beam equipped with a laser sensor and an electromagnetic actuator. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriate PID gains in nonlinear systems and systems with time variant characteristic and so on. In this paper, we design the fuzzy based PID controller of which output gains are adjusted automatically and the designed controller is applied to active vibration control of a cantilever beam using electromagnetic actuator with strong nonlinearity. The tuning PID parameters of proposed controller are determined by using Fuzzy algorithm. Effectiveness and performance of the designed controller are verified by both simulation and experiment results. Experimental results demonstrate that better control performance can be achieved in comparison with the PID cotroller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.525-528
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• 2005

The tracking antenna system must be always pointed to target moving vehicle. Especially, for an antenna mounted on a movable vehicle, it needs the stabilized antenna system. In this paper, two types of fuzzy controller were derived and applied to a data link antenna system and the altitude control of unmanned helicopter, respectively. A simplified Fuzzy-PID controller was designed for 2-axes antenna stabilization and tracking system and the performance was verified by simulations and experiments. Computer simulations were performed by Matlab and SIMULINK. A 2-Axes antenna (SeaTel 1898 model) was selected as test platform of this research. The antenna was modified by using two Blushless Direct Current motors and an embedded DSP controller. To verify the performance of designed antenna servo control system, the performance of the conventional PID controller and that of the Fuzzy-PID controller, designed by the same PID control gains, were compared.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.830-836
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• 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 Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.72-81
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• 2000

In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.115-117
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• 2019

In this paper, an intelligent control scheme based on Fuzzy PID controller is proposed for accurate power sharing in DC Microgrid. The proposed Fuzzy PID controller is designed with the aid of a closed loop control based on per unit power of each distributed generator (DG), and accurate power sharing is successfully realized in proportional to each DG's power rating regardless of the line resistance difference or the load change. Thanks to Fuzzy PID controller, the dynamic response becomes faster and the stability of the microgrid system are improved in comparison to conventional PID controller. The superiority of the proposed method is analyzed and verified by simulation in Matlab and Simulink.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.379-383
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• 2003

Parallel type fuzzy controller is designed by using a hybrid connected type fuzzy-PID controller and a model reference fuzzy controller. The first controller, consists of a fuzzy-PI and a fuzzy-PD making a hybrid type fuzzy-PID controller, plays a role as firstly reaching stable responses and secondly overcoming disturbance in plants. The second controller, model reference fuzzy controller, plays a role as reaching faster responses than other controllers. We have confirmed that the controller produces rapid and stable responses and overcomes disturbance by using parallel type fuzzy controller in a DC motor application.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2839-2842
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• 1999

This paper describes the design of fuzzy PID controller using simplified indirect inference method. First, the fuzzy PID controller is derived from the conventional continuous time linear PID controller. Then the fuzzification, control-rule base, and defuzzification using SIIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional PID controller, which has the same linear structure. but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one proposed by D. Misir et al.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2129-2131
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• 2001

Induction motor has been using for industrial field. 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 fuzzy control for optimal control of the induction motor in plant. In order to attain optimal control, flux, torque and speed controller has been used and an fuzzy logic based controller has been applied to this system. The results of the fuzzy are compared with the PID controller tuned by the Ziegler-Nickels method, through various simulation based on the various disturbance and step response. The simulation results of the fuzzy control represent a more satisfactory response than those of the conventional controllers.