• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.19-24
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• 2007

In this paper, we propose a tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller consists of the convex set of PID and PI-PD controller. PID-PD controller controls the closed-loop response to be located between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.15-22
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• 2005

In this paper, we propose a PID-PD controller and its tuning method to be modified form of PID controller that consist of the affine set of PID and PI-PD controller by analyzing relation between these controllers. The proposed tuning method controls the closed-loop system to locate between the step responses of system controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost functions. Its effectiveness is examined by the case studies and their analysis.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.628-631
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• 2005

In this paper, we propose tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller that consist of the convex set of PID and PI-PD controller controls the closed-loop response to locate between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.259-269
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• 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 Navigation and Port Research
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• v.34 no.2
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• pp.117-122
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• 2010

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains and to analyse the stability compared to conventional PID controllers. This paper proposes a fuzzy PD+I controller for tracking control which uses a linear fuzzy inference(product-sum-gravity) method based on a conventional linear PID controller. In this scheme the fuzzy PD+I controller works similar to the control performance as the linear PD plus I(PD+I) controller. Thus it is possible to analyse and design an fuzzy PD+I controller for given systems based on a linear fuzzy PD controller. The scaling factors tuning scheme, another topic of fuzzy controller design procedure, is also introduced in order to fine performance of the fuzzy PD+I controller. The scaling factors are adjusted by a real-coded genetic algorithm(RCGA) in off-line. The simulation results show the effectiveness of the proposed fuzzy PD+I controller for tracking control problems by comparing with the conventional PID controllers.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.1-8
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• 2008

A two-wheel balancing vehicle, which helps people moving freely and fast, and is applied from inverted pendulum system, has been widely researched and developed, and some products are came into a market in actuality. Until now, the two-wheel balancing vehicles developed have chosen the general PID control method. In this paper, we propose a new control method to improve a control capacity for a two-wheeled balancing vehicle for human transportation. The proposed method is the fuzzy PD+I control that is one of the improved PID control, and it contains a 2input-1output fuzzy system. This fuzzy system processes signals from proportional and derivative controller, and the fuzzy output signal generates the final output by summing up integral signal. The non-linearity of the fuzzy system makes an optimal output control signal by changing weight of the proportional signal and the derivative signal in process of time. We have simulated the fuzzy PD+I control system and experimented by implementing the two-wheel balancing mobile robot to verify the advantages of the proposed fuzzy PD+I control method in comparison with general PID control. As the results of simulation and experimentation, the proposed fuzzy PD+I control method has better control performance than general PID in this system and improves it.

• Journal of Industrial Technology
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• v.13
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• pp.43-48
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• 1993

In this paper, a new PID fuzzy controller (FC) is presented. The linguistic control rules of PID FC is separated into two parts : one is $e-{\Delta}e$ part, and the other is ${\Delta}^2e-{\Delta}e$ part. And then two FCs employing these rule base indivisually are synthesized. The control input to the process is decided by taking weighted mean of the outputs of two FCs. The proposed PID FC improve the transient response of the system and gives better performance than the conventional PI FC.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.411-419
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• 1998

In this paper the steady-state genetic algorithm is applied for the optimal design of fuzzy PID controllers. Basically the structure of the discussed fuzzy PID controller is extended from the conventional fuzzy PI and PD controllers where only a two-dimensional rule base of the fuzzy PID controller are designed simultaneously. Simulations results shows the superior performance of this optimal designed fuzzy PID controllers to the optimal designed conventional fuzzy PI and PD controllers.

• Journal of the Korea Computer Industry Society
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• v.2 no.4
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• pp.425-434
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• 2001

In this paper, a series of processes to configure a feedback control system by using a PID controller in a programmable logic controller (PLC). The PLC (SIMATIC S7-400) with a PID module (FM455C) is connected by online to an IBM PC with the Windows environment, which serves as a PLC programmer. PID controllers including P/PD/PI controllers have been designed in order to show design procedures, and finally, a PID controller for the plant of cart system. Performances of the control system have been investigated by the MATLAB simulation, the simulation in the PLC programmer. Physical performances have been recorded and examined for the real cart system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.45.1-45
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• 2001

This paper proposes a Mamdani fuzzy PID controller for controlling a process with small dead time. The controller composes of a parallel structure of fuzzy PI controller and fuzzy PD controller. Each controller has two inputs, error and change of error. Hence, the control signal of the proposed controller is the average value of the output of the fuzzy PI and PD controllers. The Mamdani fuzzy PID controller is easily to be adjusted to meet the desired control system performances both in transient state and steady state. The simulation results of the proposed Mamdani fuzzy PID controller by using the same parameters (proportional gain, integral time and derivative time) as the conventional PID controller are shown. The response of the Mamdani fuzzy PID control system is faster than the conventional PID control system. Both system responses have ...