• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.5
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• pp.78-84
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• 2001

The translation system is made up of springs, masses and a dashpot. This precise piece of equipment is controlled electro-mechanically by a motor and operating program. The control strategy of the system can be changed by spring stiffness, change of mass, and the damping coefficient of the dashpot. This system proves the necessity and effect of a closed loop control. In this paper, PD control experiments were implemented for the translation system. When the north falter was added on the PD controller, we compared the response characteristics of the two systems. The state feedback controller minimized scalar control gains and the resulting response characteristics of the system were studied using the LQR design. Finally, we improved the response characteristics of the translation system which are rising time, settling time, steady state error, and overshoot LQR was better as compared with PD control.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1101-1105
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• 2012

This study proposes a method for improvement of PD type fuzzy controller. The method includes self tuner using gradient algorithm that is one of the optimization algorithms. The proposed controller improves simple Takagi-Sugeno type FLC (Fuzzy Logic Control) system. The simple Takagi-Sugeno type FLC system changes nonlinear characteristic to linear parameters of consequent membership function. The simple FLC system could control the system by calibrating parameter of consequent membership function that changes the system response. While the determination on parameter of the simple FLC system works well only partially, the proposed method is needed to determine parameters that work for overall response. The simple FLC system doesn't predict the response characteristics. While the simple FLC system works just like proportional part of PID, our system includes derivative part to predict the next response. The proposed controller is constructed with P part and D part FLC system that characteristic parameter on system response is changed by self tuner for effective response. Since the proposed controller doesn't include integral part, it can't eliminate steady state error. So we include a gain to eliminate the steady state error.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.195-195
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• 2000

In this paper, intelligent control method using neural network as a nonlinear controller is presented, Neural network controller is implemented on DSP board in PC to make real time computing possible, On-line training algorithm for neural network control is proposed, As a test-bed, a large a-x table was build and interface with PC has been implemented, Experimental results under different PD controller gains show excellent position tracking for circular trajectory compared with those for PD controller only.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.544-547
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• 2003

The purpose of this paper is to develop the straightforward design guidelines of PD/PID speed controller for Industry servo drives with plug and play concept. The controller gains are uniquely determined from the current control loop dynamics, speed loop delay, and mechanical parameters. In order to eliminate the mechanical friction uncertainties, an automatic PD/PI control mode switching algorithm Is introduced using online spectrum analysis of motor torque command. The dynamic performance of the proposed scheme assures a fast tracking response curve with minimal oscillation and settling time over the whole operating conditions. For comprehensive comparison of conventional PI control scheme, extensive test is carried out on actual servo system.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.46-49
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• 2002

This paper presents I-PD controller design using LQR method in a two-inerita motor system to satisfy the design specification in time domain. And to provide a systematic LQ analysis for two-inerita motor system. The tuning parameters of LQ(I-PD) controller are determinated by the relationships between the design parameters of the overshoot and the settling time which are design specifications in time domain, and the weighting factors Q and R in LQR we can achieve the performance-robustness in time domain as well as the stability-robustness.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.483-483
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• 2000

The Fuzzy Preview Control (FPC) design methodology using I-PD Preview Control (IPC) and Optimal Preview Control (OPC)[6] are discussed in this paper. First we show a new fuzzy controller with single input single output, and build a relationship between it and the I-PD Control proposed by Kitamari, as well as Optimal Control with some specific equations. We also give the stability analysis with Lyapunov theorem. On this way, we can design a Fuzzy I-PD Controller (FIC) very easier and more effective. Then, preview control element design methodology of FCP was given according to IPC and OPC. Third, to make the system more rapidly and more little overshooting, two factors are given to adjust the controller's properties. At last, the performance of FPC is revealed via computer simulation using a nonlinear plant.

• 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 ...

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2322-2329
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• 2008

In this study, we introduce the design methodology of an optimized fuzzy cascade controller with the aid of particle swarm optimization(PSO) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. We introduce the fuzzy cascade controller scheme which consists of the outer(1st) controller and the inner(2nd) controller as two cascaded fuzzy controllers, and auto-tune the control parameters(scaling facrors) of each fuzzy controller using PSO. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on PSO, is presented in comparison with the conventional PD cascade controller based on serial genetic alogritms.

• 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 the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.525-531
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• 2001

The paper demonstrates that RBF(Radial Basis Function) networks can be used effective for the identification of inverted pendulum system. With the parallel arrangement of the RBF networks controller and PD controller, some characteristics were compared through simulation performance.