• Journal of Power Electronics
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• v.7 no.1
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• pp.21-27
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• 2007

This paper investigates a PID fuzzy controller for output voltage regulation of a current-doubler-rectified asymmetric half-bridge (CDRAHB) DC/DC converter. The controller is a PD-type fuzzy controller in parallel with a linear integral controller. The PD type fuzzy controller is for providing the varying gain at the different operating conditions to regulate the output voltage. The linear integral controller is for removing the steady-state error of the output voltage. In order to show the outstanding dynamic characteristics of the proposed controller, PSIM simulation studies are carried out and compared to the results for which the conventional loop gain design method is used.

• Journal of Power Electronics
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• v.16 no.2
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• pp.564-571
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• 2016

This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.326-329
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• 2003

Controller that is designed in this paper is form that apply PID controller about Fuzzy algorithm. Fuzzy Controller that using this paper is can speak that compensation style fuzzy controller as form to solidify action of PID controller for plant. This is not form that autotuning the each PID coefficient. We Apply and examined the response character to AGC(Automatic Generation Control) system using designed controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.228-231
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• 2000

A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.3
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• pp.85-92
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• 2005

Due to the friction characteristic of pump, cylinder, and between passenger car and the rail, there exist dead zone in the hydraulic system actuated with inverter, which can not be controlled by a PID controller. In this paper, the friction characteristic of a cylinder is considered first, which may cause the uncontrolled speed in the zero-crossing speed region. And then, the zooming fuzzy logic controller is designed to overcome the drawback by the existing PID speed controller. Finally, The proposed hybrid fuzzy controller is applied to the PID controller in the normal speed region and to the fuzzy controller in the zero-crossing speed region. The reason is that the problem of the uncontrolled speed in the zero-crossing speed region caused by the friction characteristic of the cylinder in hydraulic elevator can be solved, and the effectiveness of the controlling system not only in the zero-crossing speed region but also the overall controlling region including steady-state can be simulated and performed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.423-426
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• 2005

In this paper, we proposed a PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kp, $\tau_{I}$, $\tau_{D}$. by the Ziegler-Nichols formula that uses the ultimate gain and ultimate period from a relay tuning experiment. We will get the error and the error rate of plant output corresponding to the initial value of parameter and fnd the new proportion gain(Kp) and the integral time ($\tau_{I}$) from fuzzy tuner by the error and error rate of plant oueut as a membership function of fuzzy theory. This fuzzy auto tuning algorithm for PID controller considerably reduced the overshoot and rise time as compared to any other PID controller tuning algorithms. And in real parametric uncertainty systems, it constitutes an appreciable improvement of performance. The significant property of this algorithm is shown by simulation

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.444-451
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• 2007

In this paper, we propose an improved reduction model and a reduction model-based hybrid smith-predictor fuzzy controller. The transient and steady-state responsed of the reduction model was evaluated. In tuning the controller, the parameters of PID and the factors fuzzy controllers were obtained from the reduced model and by using genetic algorithms, respectively. Simulation examples demonstrated a better performance of the proposed controller than conventional ones.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1931-1932
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• 2008

To demonstration the efficiency of fuzzy logic controller, we carried out simulation with a automobile's transfer function. First, we designed the PID controller by using Ziegler-Nichols tunning method. Second, we calculated time response for each controller, then we compared the speed patterns of fuzzy controlled system and PID controlled system. Also we compared the difference of input variable. By comparing two controller's response, we can confirm the merit of fuzzy controller about comfortability. Fuzzy controller can reduce input changing frequency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.26-34
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• 2015

In this paper, a fuzzy compensated PID control system is proposed for formation control of mobile robots. The control system consists of a kinematic controller based on the leader-follower approach and a dynamic controller to handle dynamics effects of mobile robots. To maintain the desired formation of mobile robots, the dynamic controller is equipped with a PID controller; however, the PID controller has poor performance in nonlinear and changing environments. In order to improve these problem, we applied the additional fuzzy compensator. Finally, the proposed control system has been evaluated through computer simulation to demonstrate the improved results.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.226-231
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• 2016

Researching and developing mobile robot are quite important. Autonomous driving of mobile robot is important in various working environment. For its autonomous driving, mobile robot detects obstacles and avoids them. Purpose of this thesis is to analyze kinematics model of the mobile robot and show the efficiency of type-2 fuzzy self-tuning PID controller used for controling steering angle. Type-2 fuzzy is more flexible in verbal expression than type-1 fuzzy because it has multiple values unlike previous one. To compare these two controllers, this paper conduct a simulation by using MATLAB Simulink. The result shows the capability of type-2 fuzzy self-tuning PID is effective.