• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 추계학술대회 논문집
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• pp.209-214
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• 1992

This paper presents a one cycle R&D project regarding the large inertia platform servo control system. The steps followed the rather orthodox procedure. A serial double rate-loop was closed with a position loop, and acceleration velocity anticipatory compensations were designed in the forward path. Some appropriate compensation devices were utilized for the signal processing as well as for the better control quality. Simulations and experimental tests were repeated, and satisfactory performances were observed. However, frequency domain uncertainties inherent to the large structures still remain as an expertise supported subject.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.673-677
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• 1986

This paper deals with the state observer-controller which observes unmeasurable state variables of the system and then uses the estimated values as feedback signals. The linearized model is deduced from the nonlinear electrohydraulic servo system. The 4th order analog linear observer-controller and the 2nd order digital one are modelled and implemented using OP amplifiers and IBM PC/XT, respectively. The two observer are experimentally used in the control of an electrohydraulic system. The results are satisfactory in estimation performance and in tracking performance to command signal.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.186-188
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• 1995

In this paper, Cross-Coupled Controller proposed for multi axes servo system. Tracking error and contouring error exist when a machine tool moves along the trajectory in multi exes system. The proposed scheme enhances the contouring performance by reducing contour error. Feedforward compensator reduces the effects of a nonlinear disturbance such as friction or dead zone. The proposed control scheme reduces the contour error which occured when the tool tracks the reference trajectory. Simulation results show that this scheme improves the contouring performance along the reference trajectory in XY-table.

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.25-34
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• 2000

In this paper, we design a H^\infty servo controller for gauge control of tandem cold mill. To improve the performance of the AGC(Aotomatic Gauge Control) system based on the Taylor linearized model of tandem cold mill, the H^\infty servo controller is designed to satisfy robust stability, disturbance attenuation and robust tracking properties. The H^\infty servo controller problem is modified as an usual H^\infty control problem, and the solvability condition of the H^\infty servo problem depends on the solvability of the modified H^\infty control problem. Since this modified problem does not satisfied standard assumptions for the H^\infty control problem, it is solved by an LMI(Linear Matrix Inequality) technique. Consequently, the comparison between the H^\infty servo controller and the existing PID/FF(FeedForward) controller shows the usefulness of this study.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권8호
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• pp.361-366
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• 2001

This thesis proposes a fuzzy logic cross coupled controller for a multi axis servo system. The overall control system consists of three elements: the axial position controller, the speed controller, and a fuzzy logic cross coupled controller. In conventional multi axis servo system, the motion of each axis is controlled independently without regard to the motion of other axes, in which the contour error, defined as the shortest distance between the desired and actual contours is compensated only by the position error of each axis. This decoupled control approach may result in degraded contouring performance due to such factors as mismatch of axial dynamics and axial loop gains. In practice, such systems contain many uncertainties, Therefore, the multi axis servo system must receive and evaluate the motion of all axes for a better contouring accuracy. Cross coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However the existing cross coupled controllers cannot overcome friction, backlash and parameter variation. Also, since it is difficult to obtain an accurate mathematical model of multi axis system, here we investigate a fuzzy logic cross coupled controller method. Some simulations and experimental results are presented to illustrate the performance of the proposed controller.

• Journal of Power Electronics
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• 제13권1호
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• pp.139-160
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• 2013

In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2275-2278
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• 2005

In this paper, a control algorithm for a servo manipulator is focused on. A servo manipulator system has been developed for remotely handling radioactive materials in a hot cell. It is driven by servo motors. The torque from a servo motor is transferred through a reducer to the corresponding axis. The PID control algorithm is a simple and effective algorithm for such application. However, since friction degrades the algorithm's performance, friction has to be considered and compensated. The major aberrations are the positional tracking errors and the limit cycle. The authors have considered a switching term to a conventional PID algorithm to reduce the friction's effect. It has been tested by a hardware test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.1640_1641
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• 2009

Dynamic friction and force ripple are the most predominant factors that affect the positioning accuracy of permanent magnet synchronous motor(PMSM) servo drives system, and it is desirable to compensate them in finite time with a continuous control law. In this paper, based on LuGre dynamic friction model, a robust adaptive skidding mode controller is proposed to compensate the nonlinear effect of friction and force ripple. The controller scheme consists of a PD component and a robust adaptive sliding mode controller for estimating the unknown system parameter. Using Lyapunov stability theorem, asymptotic stability analysis and position tracking performance are guaranteed. Simulation results well verify the feasibility and the effectiveness of the proposed scheme for high0precision motion trajectory tracking.

• 제어로봇시스템학회논문지
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• 제7권6호
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• pp.509-517
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• 2001

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require and accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is evaluated through a series of experiments for the various types of inputs while applying disturbances to the hydraulic system. The performance of this controller was compared with those of PID and PD controllers. From these results, We observe be said that the position tracking performance of neuro-fuzzy is better those of PID and PD controllers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.228-228
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• 2000

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require an accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller Parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is obtained through a series of experiments for the various types of input while applying disturbances to the cylinder. .and performance of this controller was compared with that of PID, PD controller. As a experimental result, it can be proven that the position tracking performance of the neuro-fuzzy is better than that of PID and PD controller.