• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.189-194
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• 1994

Adaptive control systems based upon the command generator tracker(CGT) approach have attracted considerable interest because of the simple structure of its adaptive controller. Some attempts to such improve the adaptive control algorithm, for the sake of the application to broader class of plants, are made. Recently, Su and Sobel(1992) proposed that those schemes can be treated by an unified theory using a metasystem representation with some types of supplementary dynamics. However, in their method, it is difficult to find the dynamic compensator, which is proper and output feedback stabilizable, for the uncertain plant. This paper proposes a new design method of such supplementary dynamics and some parameters of adaptive control system for linear time invariant SISO plants. The method gives a concrete and systematic design method using only a few priori knowledge of the plant.

• Transactions of The Korea Fluid Power Systems Society
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• v.8 no.2
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• pp.23-28
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• 2011

This paper investigates the motion control of a hydraulic motor-load system using the Simple Adaptive Control (SAC) method. The plant transfer function has been modelled mathematically. The open-loop responses have been obtained experimentally in order to identify the design parameters of transfer function. The hydraulic motor-load system has been modelled using the 3D CAD and imbedded in the hydraulic circuit simulation program to verify the overall performance. The experimental results confirm that the SAC method gives a good tracking performance compared to the PID control.

• Smart Structures and Systems
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• v.10 no.1
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• pp.33-46
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• 2012

To reduce the vibration of cable-stayed bridges, conventional magnetorheological (MR) damper control system (CMRDS), with separate power supply, sensors and controllers, is widely investigated. In this paper, to improve the reliability and performance of the control system, one adaptive MR damper control system (AMRDS) consisting of MR damper and piezoelectric energy harvester (PEH) is proposed. According to piezoelectric effect, PEH can produce energy for powering MR damper. The energy is proportional to the product of the cable displacement and velocity. Due to the damping force changing with the energy, the new system can be adjustable to reduce the cable vibration. Compared with CMRDS, the new system is structurally simplified, replacing external sensor, power supply and controller with PEH. In the paper, taking the N26 cable of Shandong Binzhou Yellow River Bridge as example, the design method for the whole AMRDS is given, and simple formulas for PEH are derived. To verify the effectiveness of the proposed adaptive control system, the performance is compared with active control case and simple Bang-Bang semi-active control case. It is shown that AMRDS is better than simple Bang-Bang semi-active control case, and still needed to be improved in comparison with active control case.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.472-477
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• 1996

This paper presents a new approachtothe design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The prpposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• 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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• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.154-161
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• 1999

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.79-84
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.26-37
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller. feedback controller. and PID type time-varying auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.