• 한국정밀공학회지
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• 제23권9호
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• pp.92-101
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• 2006

In this paper a adaptive backstepping control scheme is proposed for control of a do motor driving a one-link manipulator. Fuzzy logic systems are used to approximate the unknown nonlinear function including the parametric uncertainty and disturbance throughout the entire electromechanical system. A compensation controller is also proposed to estimate the bound of approximation error. Thus the asymptotic stability of the closed-loop control system can be obtained. Numerical simulations are included to show the effectiveness of the proposed controller.

• Journal of Power Electronics
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• 제19권5호
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• pp.1193-1202
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• 2019

A SMPMSM drive system is a typical nonlinear system with time-varying parameters and unmodeled dynamics. The speed outer loop and current inner loop control structures are coupled and coexist with various disturbances, which makes the speed control of SMPMSM drive systems challenging. First, an ultra-local model of a PMSM driving system is established online based on the algebraic estimation method of model-free control. Second, based on the backstepping control framework, model-free adaptive integral backstepping (MF-AIB) control is proposed. This scheme is applied to the permanent magnet synchronous motor (PMSM) drive system of an electric vehicle for the first time. The validity of the proposed control scheme is verified by system simulations and experimental results obtained from a SMPMSM drive system bench test.

• Journal of Power Electronics
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• 제18권5호
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• pp.1380-1397
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• 2018

The synchronous reluctance motor (SynRM) servo-drive system has highly nonlinear uncertainties owing to a convex construction effect. It is difficult for the linear control method to achieve good performance for the SynRM drive system. The nonlinear backstepping control system using upper bound with switching function is proposed to inhibit uncertainty action for controlling the SynRM drive system. However, this method uses a large upper bound with a switching function, which results in a large chattering. In order to reduce this chattering, a nonlinear backstepping control system using an adaptive law is proposed to estimate the lumped uncertainty. Since this method uses an adaptive law, it cannot achiever satisfactory performance. Therefore, a nonlinear backstepping control system using a reformed recurrent Hermite polynomial neural network with an adaptive law and an error estimated law is proposed to estimate the lumped uncertainty and to compensate the estimated error in order to enhance the robustness of the SynRM drive system. Further, the reformed recurrent Hermite polynomial neural network with two learning rates is derived according to an increment type Lyapunov function to speed-up the parameter convergence. Finally, some experimental results and a comparative analysis are presented to verify that the proposed control system has better control performance for controlling SynRM drive systems.

• Journal of Power Electronics
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• 제16권2호
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• pp.598-609
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• 2016

The good control performance of permanent magnet linear synchronous motor (LSM) drive systems is difficult to achieve using linear controllers because of uncertainty effects, such as fictitious forces. A backstepping control system using adaptive modified recurrent Laguerre orthogonal polynomial neural network uncertainty observer (OPNNUO) is proposed to increase the robustness of LSM drive systems. First, a field-oriented mechanism is applied to formulate a dynamic equation for an LSM drive system. Second, a backstepping approach is proposed to control the motion of the LSM drive system. With the proposed backstepping control system, the mover position of the LSM drive achieves good transient control performance and robustness. As the LSM drive system is prone to nonlinear and time-varying uncertainties, an adaptive modified recurrent Laguerre OPNNUO is proposed to estimate lumped uncertainties and thereby enhance the robustness of the LSM drive system. The on-line parameter training methodology of the modified recurrent Laguerre OPNN is based on the Lyapunov stability theorem. Furthermore, two optimal learning rates of the modified recurrent Laguerre OPNN are derived to accelerate parameter convergence. Finally, the effectiveness of the proposed control system is verified by experimental results.

• 한국정밀공학회지
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• 제25권6호
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• pp.62-70
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• 2008

An adaptive fuzzy backstepping controller is proposed for the motion control for a single-link flexible-joint robot in the presence of parametric uncertainties. Fuzzy logic system is used to approximate the uncertainties of functions and a backstepping technique is employed to deal with the mismatched problem. A compensation controller is also employed to estimates the bound of approximation error so that the shattering effect of the control effort can be reduced. Thus the asymptotic stability of the closed loop control system can be obtained based on a Lyapunov synthesis approach. Numerical simulation results for a single-link flexible-joint robot are included to show the effectiveness of proposed controller.

• 대한기계학회논문집A
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• 제28권12호
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• pp.1833-1844
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• 2004

A controller is proposed for the robust backstepping control of a class of nonlinear multiple-input multiple-output (MIMO) systems which can be converted to a strict feedback form. The proposed robust backstepping control scheme follows a systematic procedure for the design of control laws and uses time delay estimation (TDE) to estimate the uncertainties such as parameter variations, unknown disturbances, and unmodeled dynamics, etc. The proposed controller can be also applied to nonlinear MIMO systems with unmatched uncertainties. Stability analysis of the closed-loop system which contains the plant and the proposed controller is also studied and hereby a sufficient stability condition for the closed-loop system is proposed. The simulation results show that the control scheme works well with uncertainties and the proposed stability condition is valid. The controller is experimentally verified on a single-link flexible arm to show the effectiveness of the proposed scheme in the complicated systems with uncertainties.

• 한국해양공학회지
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• 제32권2호
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• pp.131-137
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• 2018

In this paper, we propose an adaptive backstepping controller to control the exact position and orientation of a remotely operated underwater vehicle with parametric model uncertainty. To further improve the angular velocity control precision of each thruster, a phase locked loop (PLL) controller has been added to the backstepping controller. A comparison of two backstepping controllers with and without the PLL control loop has been performed using simulations and experiments. The test results showed that the tracking performance could be improved by using the PLL control loop in the proposed adaptive backstepping controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.37.5-37
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• 2001

A robust control for robot manipulators actuated by induction motors using neural networks(NNs) is considered. The control is designed to compensate for nonlinear dynamics associated with the mechanical subsystem and the electrical subsystems only with the measurements of link position, link velocity and stator winding currents. Two-layer NNs are used to approximate unknown functions occurring from parameter variation during backstepping design process. Specially, through the use of nonlinear observers for rotor flux, observed backstepping controller is designed to achieve uniform ultimately bounded link position tracking of the given reference signal ...

• 대한전기학회논문지:시스템및제어부문D
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• 제55권11호
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• pp.476-482
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• 2006

Based on a field-oriented model of induction motor, an adaptive backstepping control approach using neural networks is proposed in this paper for the speed control of induction motors with uncertainties at a minimum of information. Neural networks are used to approximate most of uncertainties which are derived from unknown motor parameters, load torque disturbances and unknown nonlinearities and an adaptive backstepping controller is used to derive adaptive law of neural networks and control input directly. The controller is implemented by the hardware using DSP and the effectiveness of the proposed approach is verified by carrying out the experiment.

• 한국정보통신학회논문지
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• 제19권8호
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• pp.1874-1882
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• 2015

본 논문에서는 PID 적분슬라이딩모드를 이용한 IPMSM의 백스태핑제어를 제안한다. IPMSM에 슬라이딩모드를 이용함에 있어서 부하외란의 비정합성에 대한 걸림돌을 제거하기 위해 백스테핑기법을 적용한다. 슬라이딩모드제어기를 백스테핑에 적용시키는데 있어서의 어려움인 오차모델의 유도를 피하기 위하여 PID제어기와 적분슬라이딩모드를 결합한다. 결과적인 제어기의 형태는 기존의 PID제어 구조에 슬라이딩모드입력을 추가하는 형태로 구성되며 실제적인 적용에 있어서도 매우 유리한 구조이다.