• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.420-427
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• 2007

This paper highlights the comparison of a proposed methods named adaptive undervoltage load shedding based PTSI techniques for undervoltage load shedding and two previous methods named Fixed Shed Fixed Delay (FSFD) and Variable Shed Variable Delay (VSVD) for avoiding voltage collapse. There are three main area considerations in load shedding schemes as the amount of load to be shed, the timing of load shedding event, and the location where load shed is to be shed. The proposed method, named as adaptive UVLS based PTSI seem to be most appropriate among the uncoordinated schemes. From the simulation result can be shown the Adaptive UVLS based PTSI give faster response, accurate and very sensitive control for the UVLS control technique. This technique is effectively when calculating the amount to be shed. Therefore, it is possible to bring the voltage to the threshold value in one step. Thus, the adaptive load shedding can effectively reduce the computational time for control strategy.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2087-2088
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• 2001

In this paper we presents a speed controller for permanent magnet synchronous motor using adaptive backstepping technique. The adaptive backstepping technique takes system nonlinearity into account in the control system design stage. The proposed control and adaptive law is proved to be asymptotically stable by the Lyapunov stability theory.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2540-2545
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• 2003

We propose a new technique to the design and real-time implementation of an adaptive controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs(TMS320C80) 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 a dual arm robot consisting of two 4-d.o.f. robots at the joint space and cartesian space.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.160-163
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• 1988

In this paper, the adaptive controller for the turret gun is discussed which uses model reference adaptive technique based on the Lyapunov direct method. Turret gun can be decomposed into two time-invariant SISO control systems. One is for the elevation angle control and the other is for the azimuth angle control under the assumption of independence each other. Thus we only consider here about the control loop for the elevation angle.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.148-153
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• 1999

In this paper, it is proposed the adaptive-sliding mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Over the past decade, the design of advanced control systems for industrial robotic manipulators has been a very active area of research and two major design categories have emerged. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in continuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple structure is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results how that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.741-746
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• 2004

We propose a new technique to the design and real-time implementation of an adaptive controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs(TMS320C80) 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 a dual arm robot consisting of two 4-d.o.f. robots at the joint space and cartesian space.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.51-55
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• 2006

An adaptive tracking controller is presented for the vibration reduction of flexible manipulator employed in hazardous area by combining input shaping technique with sliding-mode control. The combined approach appears to be robust in the presence of severe disturbance and unknown parameter which will be estimated by least-square method in real time. In a maneuver strategy, it is found that a hybrid trajectory with a combination of low frequency mode and rigid-body mode results in better performance and is more efficient than the traditional rigid body trajectory alone which many researchers have employed. The feasibility of the adaptive tracking control approach is demonstrated by applying it to the simplified model of robot system. For the applications of the proposed technique to realistic systems, several requirements are discussed such as control stability and large system order resulted from finite element modeling.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.71.3-71
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• 2001

Passive Stabilization method and active stabilization method are mainly used to comprise a control system of platform stabilizer. Passive Stabilization method has demerits because of size and weight except that control structure is simple while active stabilization method using sensors can reduce size and weight, it requires high sensor technique and control algorithm. In this paper, a stabilizing controller using adaptive fuzzy control technique and floating-point processor(DSP) is suggested.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.108.2-108
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• 2001

This paper presents the application of adaptive phase-locked loop (adaptive PLL) technique to control the process variable of the process control system. The adaptive algorithm is related to the error. When the error of the system is changed, the adaptive gain will be directly changed according to the error. If the value of the adaptive gain is large, the value of the error will be large. In this experiment, the reference input is 50% step input. The experimental result in controlling the first order lag process by the adaptive PLL shows that the response of the controlled system has no overshoot, short rise time, and zero steady-state error. The experimental result also shows that when the output disturbance enters to the process control system, the adaptive PLL can maintain the stability of the system and the effect of the output disturbance can also be fast rejected. The adaptive PLL has better performance ...