• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.612-619
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• 2005

A robust adaptive speed sensorless induction motor direct torque control (DTC) using a neural network (NN) is presented in this paper. The inherent lumped uncertainties of the induction motor DTC system such as parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN. An additional robust control term is introduced to compensate for the reconstruction error. A control law and adaptive laws for the weights in the NN, as well as the bounding constant of the lumped uncertainties are established so that the whole closed-loop system is stable in the sense of Lyapunov. The effect of the speed estimation error is analyzed, and the stability proof of the control system is also proved. Experimental results as well as computer simulations are presented to show the validity and efficiency of the proposed system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.1-9
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• 1989

The convergence analysis of adavtive control schemes has been studied over the past decades, but the importance of structure to fast conversgece of adaptive control systems is still a controversial issue. This paper deals with the relative improvement of the exponential rate of convergence in adaptive error models. The Lyapunov's direct method is applied to adaptive control systems in order to improve the convergence rate by modifying the feedback structure of the error systems. Some simulation examples are illustrated to show fast convergence and robustness of these schemes.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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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.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.51-52
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• 2008

In this paper, we propose two control schemes. The first control scheme is an adaptive passivity-based excitation control which regulates the terminal voltage to its reference. This controller is obtained through two steps: firstly, a simple direct adaptive passivation controller is designed for the power system with parametric uncertainties; then a linear PI controller is applied to converge the terminal voltage to its reference. The second control scheme is a linear governor control which consists of the frequency and the mechanical power. It is shown that the internal dynamics are locally stable with controllable damping. In the end, the boundness of all electrical variables, the frequency, the mechanical power, and the convergence of the terminal voltage to its reference can be achieved by these control schemes.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.866-870
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• 1989

Direct application of adaptive algorithm to the actual I/O is not a good strategy. The importance of using a kind of filter for estimation or control is strongly recommended. Simple pre-filtering method and pseudo-plant method is introduced. And, the properties of each methods are compared by analysis and/or simulations. A guideline for the choice of filters are proposed.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.6 s.183
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• pp.64-71
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• 2006

A target of this paper is to study on the usefulness of the adaptive piezoelectric energy harvesting device as a wireless electrical power supply when it is driven by mechanical vibrations of low frequency. For this purpose, an adaptive control technique and a step-down converter are used. A THUNDER series a piezoelectric material (TH7-R), which has been developed by a NASA engineer is selected for this study. In order to provide a mechanical energy to the piezoelectric material, a mechanical motion vibrator is designed. The adaptive controller is implemented using a dSPACE DS1104 controller board. The do-dc converter with an adaptive control technique harvests energy at over five times the rate of direct charging without a converter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.990-998
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• 2007

Adaptive output feedback control technique using Neural Networks(NN) is proposed for uncertain nonlinear Multi-Input Multi-Output(MIMO) systems. Modified Dynamic Inversion Model(MDIM) is introduced to decouple uncertain nonlinearities from inversion-based control input. MDIM consists of approximated dynamic inversion model and inversion model error. One NN is applied to compensate the MDIM of the system. The output of the NN augments the tracking controller which is based upon a filtered error approximation with online weight adaptation laws which are derived from Lyapunov's direct method to guarantee tracking performance and ultimate boundedness. Several numerical results are illustrated in the simulation of Van der Pol system and unmanned helicopter with model uncertainties.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.3
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• pp.291-300
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• 1990

This paper presents a robust discrete-time direct adaptive pole-placement with new discrete parameter adaptation algorithm (PAA), the standard RLS is suitably modified by adding a term which is exponentially proportional to the filtered tracking error and using a signal normalization. It is shown that it makes the overall adaptive system more robust in the presence of disturbances or unmodeled dynamics. In order to discuss the robustness improvement by using the input-output stability theory, the overall adaptive control system is reformulated and the sector theory is applied. In addition, computer simulation results are presented to complement the theoretical development.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.51-57
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• 2014

This paper presents a synchronizing adaptive feedforward control for clamping servomechanism of injection molding machines. Based on MBS, virtual design model has been developed for a direct forcing clamping mechanism. A synchronizing controller is designed and combined with adaptive feedforward control to accommodate mismatches between the real plant and the linear plant model used. From tracking control simulations, it is shown that significant reduction in position tracking error is achieved through the use of proposed control scheme.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.144-147
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• 2006

A proportional intergral (PI) control strategy is commonly used for constant current and extinction angle control in a HVDC (High Voltage Direct Current) system. A PI control strategy is based on a stactic design where the gains of a PI controller are fixed. Since the response of a HVDC plant dynamically changes with variations in the operation point a PI controller performance is far from optimum. The contribution of this paper is the presentation of the design of a rough set based, fuzzy adaptive control scheme. Experimental results that compare the performance of the adaptive control and PI control schemes are also given.