• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.3
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• pp.247-255
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• 1989

This paper proposes an error model with integral action and a pole-place-ment self-tuning controller for robot manipulators in task coordinates. The controller can reject the offset due to any load disturbance without a detailed description of the robot dynamics. The error model parameters are estimated by the recursive least square identification algorithms, and controller parameters are determined by the pole-placement method. A computer simulation study has been conducted to demonstrate the performance of the proposed control system in task coordinates for a 3-joint and 2-link spatial robot manipulator with payload.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.197-205
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• 2014

In applications of adaptive noise control or active noise control, the presence of a transfer function in the secondary path following the adaptive controller and the error path, been shown to generally degrade the performance of the Least Mean Square (LMS) algorithm. Thus, the convergence rate is lowered, the residual power is increased, and the algorithm can become unstable. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used. But these algorithms have slow convergence speed and weakness in the environment that the secondary path and error path are varied. Therefore, I present the new algorithm called the "Bi-directional Filtered-x (BFX) LMS" algorithm with nearly equal computation complexity. Through experimental study, the proposed BFX-LMS algorithm has better convergence speed and better performance than the conventional FX-LMS algorithm, especially when the secondary path or error path is varied and the impulsive disturbance is flow in.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.478-484
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• 1990

An automatic tuning method of a PID controller which is used for single input single output processes is proposed. In the proposed tuning method, the frequency response data model is adopted along with the performance index which is an integral of time weighted square error between reference model and process frequency response data model for tuning. This method is easier to retune when either the process dynamics is changed or the reference model is changed. Finally, an example is provided to show the usefulness of the method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.11
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• pp.68-76
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• 2014

This paper presents an offset error compensation algorithm for the accurate phase angle of the grid voltage in single-phase grid-connected inverters. The offset error generated from the grid voltage measurement process cause the fundamental harmonic component with grid frequency in the synchronous reference frame phase lock loop (PLL). As a result, the grid angle is distorted and the power quality in power systems is degraded. In addition, the dq-axis currents in the synchronous reference frame and phase current have the dc component, first and second order ripples compared with the grid frequency under the distorted grid angle. In this paper, the effects of the offset and scaling errors are analyzed based on the synchronous reference frame PLL. Particularly, the offset error can be estimated from the integrator output of the synchronous reference frame PLL and compensated by using proportional-integral controller. Moreover, the RMS (Root Mean Square) function is proposed to detect the offset error component. The effectiveness of the proposed algorithm is verified through simulation and experiment results.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.107-113
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• 1997

This paper presents the active control of a flexible cantilever beam vibration. The cantilever beam was excitied by a steady-state harmonic and white noise point force and the control was performed by one piezo ceramic actuator bonded to the surface of the beam. An adaptive controller based on filtered-x LMS algorithm was used and the controller was defined by minimizing the square of the response of error sensor. In the experiment, gap sensor was used as an error sensor while the sinusoidal or white noise was applied as a disturbance. In the case of sinusoidal input, more than 20 dB of vibration reduction was achieved over all range of the natural frequencies and it takes 5 seconds to control the vibration at first natural frequency and 1 second at other natural frequencies. In the case of white noise input, 7 dB of vibration reduction was achieved at the first natural frequency and good control performance was achieved in the considered whole frequency range. Results indicate that the vibration of a flexible cantilever beam could be controlled effectively when the piezo ceramic actuator was used with filtered-x LMS algorithm.

• Transactions of The Korea Fluid Power Systems Society
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• v.7 no.4
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• pp.23-31
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• 2010

As the analysis and design technologies for electro-magnetic actuation has advanced over the years, proportional solenoid valve is gaining acceptance in wide range of industrial and commercial applications because of its superior characteristics over the conventional AOV or MOV, such as improved performance, reduced maintenance costs. This research deals with the position controller design of two-stage flow control solenoid valve. Investigation of steady-state characteristics and dynamic model identification for pilot disc is performed. Least square method to minimize the error magnitude of frequency response between the closed-loop and target system is applied to the design of PI-controller gains. From the experiments of step and frequency response, it is concluded that the controller meets the performance specification of target system, which verifies the usefulness of controller design method for proportional solenoid valve.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.305-344
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• 2008

This paper presents the active control of flexible beam vibration. The beam was excited by a steady-state point force by mini shaker and the control was performed by mini shaker. To perform active control, least-mean-square (LMS) algorithm was used because it can easily obtain the complex transfer function in real-time. So an adaptive controller based on Filtered-X LMS algorithm was used and the controller was defined by minimizing the square of the response at a location of error sensor. In order to fine out performance tendency, input amplitude was changed in several cases and active vibration control was performed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.133-142
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• 2014

The least mean square(LMS) algorithm has been popular owing to its simplicity, stability, and availability to implement. But it inherently has a problem of slow convergence speed, and the presence of a transfer function in the secondary path following the adaptive controller and the error path has been shown to generally degrade the stability and the performance of the LMS algorithm in applications of acoustical noise control. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used and the bi-directional Filtered-x LMS(BFXLMS) algorithm is very attractive among them, which increase the convergence speed and the performance of the controller with nearly equivalent computation complexity. In this paper, a mathematical analysis for the BFXLMS algorithm is presented. In terms of view points of time domain, frequency domain, and stochastic domain, the characteristics and stabilities of algorithm is accurately analyzed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1234-1238
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• 2004

A Controlled neural networks are proposed in order to measure nonlinear environments in adaptive and in realtime. The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between tile output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models. To show the performance of this one, we have various experiments. And this controller call prove effectively to be control in the environments of various systems.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.434-439
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• 1997

This paper presents the active control of a flexible plate vibration. The plate was excited by white noise point force and the control was performed by one or two piezo ceramic actuator bonded to the surface of the plate. An adaptive controller based on filtered-x or multiple filtered-x LMS algorithm was used and the controller was defined by minimizing the square of the response of error sensor. In the experiment, PZT sensor was used as an error sensor while white noise was applied as a disturbance. In the case of multiple channel control, more than 22 dB of vibration reduction was achieved. Results indicate that the vibration of a flexible plate could be controlled effectively when the piezo ceramic actuator was used with multiple filtered-x LMS algorithm.