• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.11-16
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• 1998

In this paper, simultaneous estimation of rotor speed and time constant for a voltage source inverter (VSI) fed induction motor drive are disccussed. The theory is based on the Model Reference Adaptive System (MRAS). The identifier executes Simultaneous rotor speed and time constant so that vector control of the induction may be achieved in the rotor-flux oriented reference frame. Furthermore, to eliminate the offset error caused by the change in the stator resistance, a fuzzy resistance regulator is also designed which operates in parallel with the rotor speed and time constant identifier

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.12
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• pp.894-902
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• 1988

In this paper, a method for the design of robust adaptive controller using the heuristic rules of industrial engineers is presented. This scheme works on the basis of heuristic rules and includes a supervisor, a system identifier and a detuner. The supervisor detects onsetting instability based on the analysis of the amplitude and the trend of error signal, also selects running controllers. Upon detecting instability, the controller is switched to a PID algorithm and run recursively until stability is restored. Simultaneously, new input / output data is gathered and the system identifier runs to get critical sensitivity (kc) and critical period(tc). Based on the new values(kc, tc), a GPC controller is redesigned and normal GPC is finally run. The algorithm described in this paper belongs to the supervised adaptive control category with a limited use of heuristic rules. Finally, we show the robust of this scheme by simulated example.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.588-591
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• 1998

In this paper, we present a robust adaptive backstepping output feedback controller for nonlinear systems perturbed by unmodelled dynamics and disturbances. Especially, backstepping technique with modular approach is used to separately design controller and identifier. The design of identifier is based on the observer-based scheme which possesses a strict passivity property of observer error system. We will use Switching-${\sigma}$ modification at the update law and the modified control law to attenuate the effects of undodelled dynamics and disturbances for nonlinear systems.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.337-340
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• 1997

In this paper we propose direct and indirect adaptive controllers for a nonlinear multivariable steam generating unit(200MW). In the direct adaptive scheme the estimation of the controller parameter are achieved from tracking error, while in the indirect approach the unknown parameter of the boiler system is estimated by the Hopfield network-based identifier. The performance of two proposed adaptive controllers is shown through simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.222-226
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• 1992

In this study, the technique of adaptive control based on certainty equibalence for input-output linerization of nonlinear system is investigated. It is shown that the upper bound of the parameter estimation error can be represented more explicitly than Teel et al's works. Another direct approach, which shows that the adaptive input-output linearing control laws using the normalized identifier yield bounded tracking is also presented.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.4
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• pp.100-108
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• 1992

In this study, the technique of adaptive control based on certainty equivalence for the input-output linearization of nonlinear system is investigated. It is shown that the upper bound of the parameter estimation error can be represented more explicitly than Teel et al's works. Another direct approach, which stows that the adaptive input-output linearing control laws using the normalized identifier yield bounded tracing, is also presented.

• Journal of the Korean Institute of Navigation
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• v.21 no.3
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• pp.55-66
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• 1997

In this paper, applications of neural networks to vibration control of flexible single link robot manipulator are ocnsidered. The architecture of neural networks is a hidden layer, which is comprised of self-recurrent one. Tow neural networks are utilized in a control system ; one as an identifier is called neuro identifier and the othe ra s a controller is called neuro controller. The neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by dynamic error-backpropagation algorithm(DEA). To guarantee concegence and to get faster learning, an approach that uses adaptive learning rates is developed by introducing a Lyapunov function. When a flexible manipulator is ratated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlle dinsuch as way, that the motor is rotated by a specified angle. while simulataneously stabilizing vibration of the flexible manipulators so that it is arrested as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large body motions, as well as the flexural vibrations. Therefore, dynamic models for a flexible single link manipulator is derived, and LQR controller and nerual networks controller are composed. The effectiveness of the proposed nerual networks control system is confirmed by experiments.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.35-42
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• 1998

Finding a technique to achieve high machining precision and high productivity is an important issue for CNC machining. One of the solutions to meet better performance of machining is feedrate control. In this paper we present an adaptive feedrate neuro-control method for high precision and high speed machining. The adaptive neuro-control architecture consists of a neural network identifier(NNI) and an iterative learning control algorithm with inversion of the NNI. The NNI is an identifier for the nonlinear characteristics of feedrate and contour error, which is utilized in iterative learning for adaptive feedrate control with specified contour error tolerance. The proposed neuro-control method has been successfully evaluated for machining circular, corner and involute contours by computer simulations.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.259-267
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• 2014

This paper presents a simple, consistent and reliable technique to identify detected partial discharges (PD) using an acoustic ultrasonic method. A new reliable algorithm named 'Simple Partial Discharge Identifier' (SPDI) is proposed to perform identification process of the detected ultrasonic signals of PD. Experimental works based on recommended practices were setup and the ultrasonic signals of the PD were recorded. The PD data is then employed as the reference data. The SPDI developed has been tested against commonly used models in Neural Network (NN). Results from the SPDI algorithm shows more reliable results compared to NN models results. Comparison made on the mean square error (MSE) results shows SPDI produces the desired outcome with lower MSE in 97.17% of trials. Low error of SPDI indicates a high reliability to be applied in the identification of PD.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.141-148
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• 2023

During the medical data transmissions, the protection of the patient information is vital. Hence this work proposes a spatial domain watermarking algorithm that enhances the data payload (capacity) while maintaining the authentication and data hiding. The code is distributed at every pixel of the digital image and not only in the regions of non-interest pixels. But the image details are still preserved. The performance of the proposed algorithm is evaluated using several performance measures such as the mean square error (MSE), the mean absolute error (MAE), and the peak signal to noise Ratio (PSNR), the universal image quality index (UIQI) and the structural similarity index (SSIM).