• Journal of the Korean Society of Industry Convergence
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• 제18권3호
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• pp.139-149
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• 2015

In this paper, we describe a new approach to perform real-time implementation of an robust controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for robot manipulator consisting of dual arm with eight degrees of freedom at the joint space and cartesian space.

• Journal of Institute of Control, Robotics and Systems
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• 제12권3호
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• pp.233-240
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• 2006

This paper presents the robust control method using a self recurrent wavelet neural network (SRWNN) via adaptive backstepping design technique for stable walking of biped robots with unknown model uncertainties. The SRWNN, which has the properties such as fast convergence and simple structure, is used as the uncertainty observer of the biped robots. The adaptation laws for weights of the SRWNN and reconstruction error compensator are induced from the Lyapunov stability theorem, which are used for on-line controlling biped robots. Computer simulations of a five-link biped robot with unknown model uncertainties verify the validity of the proposed control system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1047-1051
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• 1993

A fuzzy controller of a manipulator with artificial rubber muscles is proposed. The fuzzy logic controller as a compensator is described to control the trajectory tracking of a -two link manipulator, where computed torque control method has already assumed to be applied. We shows that the fuzzy compensator with a simple adaptive scaling technique is effective for the robust control when there exist model uncertainties and/or untuned feedback gains. The effectiveness of the proposed control method is illustrated by some experimental results for a circular path tracking.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1016-1026
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• 2017

An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

• Proceedings of the KIEE Conference
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.81-84
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• 1990

This paper presents a method of sub-optimal control for nonlinear systems via block pulse transformation. The adaptive optimal control scheme proposed by J.P. Matuszewski is introduced to minimize the performance index. The proposed method is simple and computationally advantageous. Viablity of the this method is established with simulation results for the van der Pole equation for comparision with other methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• 제30B권7호
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• pp.31-41
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• 1993

In this paper, a fuzzy adaptive controller is proposed for the process with large delay time and unmodelled dynamics. The fuzzy adaptive controller consists of self tuning controller and fuzzy tuning part. The self tuning controller is designed with the continuous time GMV (generalized minimum variance) using emulator and weighted least square method. It is realized by the hybrid method. The controller has robust characteristics by adapting the inference rule in design parameters. The inference processing is tuned according to the operating point of the process having the nonlinear characteristics considering the practical application. We review the characteristics of the fuzzy adaptive controller through the simulation. The controller is applied to practical electric furnace. As a result, the fuzzy adaptive controller shows the better characteristics than the simple numeric self tuning controller and the PI controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• 제38권11호
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• pp.905-912
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• 1989

An adaptive control scheme is presented for uncertain systems whose uncertainties are upper-bounded by a linear combination of unknown constants and known continuous functions. The state of the closed-loop system is proven to be ultimately bounded. The proposed method modifies the method of Corless and Leitmann in the following two respects. First, the linear region of the saturation function in controller is fixed. Second, the intergration from in parameter estimator is replaced by a low pass filter form. These modifications prevent performance degradation and destabilization of the control system more effectively. The norm of the system states can be made sufficiently small by an appropriate choice of design parameters in the control law. The applicability of the proposed scheme is demonstrated in the position control of a simple pendulum via simulation.

• Proceedings of the KIEE Conference
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• 대한전기학회 2002년도 하계학술대회 논문집 B
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• pp.1084-1087
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• 2002

This paper presents an improved fuzzy logic-based adaptive PWM technique. A fuzzy logic- based adaptive PWM technique determines the optimal output voltage vector which takes into account both direction of back-emf and direction of current error vector. This technique has a simple structure and a good level of stability, but it has disadvantages. The longer sampling period, the larger current error. Because there is no considerations of the current error magnitude of each phases. The proposed method improves the control performance by selecting the optimum switching pattern in which the magnitudes of current errors are considered introducing space vector concept. Simulation results using Matlab/Simulink show that the proposed control method reduces current error keeping the merit of previous one.

• Transactions of the Korean Society of Mechanical Engineers
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• 제8권1호
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• pp.65-70
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• 1984

A recursive parameter estimation method is applied to spindle deflection model during boring process. The spindle infeed rate is then determined to preserve the diametral tolerance of bore. This estimation method is further extended to adaptive control by application of the variance perturbation method. The results of computer simulation attest that the proposed method renders the optimal cutting conditions, maintaining the diametral accuracy of bore, regardless of parameter fluctuations. The proposed method necessitating only post-process measurements features that initialization of parameter guess values in simple, a priori knowledge on parameter variations is not needed and the accurate estimation of optimal spindle infeed rate is obtained, even if the parameter estimation may be poor.

• The Transactions of the Korean Institute of Electrical Engineers
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• 제32권4호
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• pp.136-144
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• 1983

In this paper, a new scheme of implicit MRAC is presented for single input single output discrete system. The MRAC can be applied to the nonminimum phase system, too. They have simple structure because the parameters of the controller are estimated directly by changing the plant output equation properly. In this scheme, the observation process is well seperated from the adaptation process, so the adaptation algorithm is derived from the exponentially weighted least square method which has fast convergence characteristics and can deal with the time varying plant. The consistency of the estimated parameter is proved. And it is also proved the whole system has the stabilizing property. The effectiveness of the algorithm and the structure is illustrated by the computer simulation of the model reference adaptive control for a third order plant. It is proposed how to select the selectable parameters in the adaptive control system from the simulation results.