• Journal of Ocean Engineering and Technology
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• v.32 no.2
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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.

• Journal of Power Electronics
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• v.18 no.5
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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.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.163-172
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• 2014

This paper proposes a novel guidance law based on the block backstepping sliding mode control and extended state observer (ESO), which also takes into account the autopilot dynamic characteristics of the near space interceptor (NSI), and the impact angle constraint of attacking the maneuvering target. Based on the backstepping control approach, the target maneuvers and the parameter uncertainties of the autopilot are regarded as disturbances of the outer loop and inner loop, respectively. Then, the ESO is constructed to estimate the target acceleration and the inner loop disturbance, and the block backstepping sliding model guidance law is employed, based on the estimated disturbance value. Furthermore, in order to avoid the "explosion of complexity" problem, first-order low-pass filters are also introduced, to obtain differentiations of the virtual control variables. The stability of the closed-loop guidance system is also proven, based on the Lyapunov theory. Finally, simulation results demonstrate that the proposed guidance law can not only overcome the influence of the autopilot dynamic delay and target maneuvers, but also obtain a small miss distance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1874-1882
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• 2015

In this paper, robust backstepping controller for IPMSM is proposed based on the PID integral sliding mode control. Because of the unmatching condition of load, the sliding mode control is difficult to be used for IPMSM without backstepping. However, the backstepping control has the difficulty of deriving error dynamics which is derived by differentiating the previous input. This difficulty is avoided by adopting PID as a nominal controller for the integral sliding mode control. The proposed controller can be achieved easily by adding integral sliding controller to the conventional PID controller.

• Journal of Power Electronics
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• v.16 no.2
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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.

• Journal of Ocean Engineering and Technology
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• v.25 no.5
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• pp.1-8
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• 2011

This paper proposes a controller design for an omnidirectional mobile platform (OMP) with three wheels using backstepping control. A kinematic model and dynamic model of the system are presented. Based on the dynamic modeling, a backstepping controller is designed to stabilize the OMP when following a desired path. The controller is designed based on a backstepping control theory. It includes two steps: first, a virtual state and a stability function are introduced. Second, Lyapunov functions for the system are chosen and an equation for the virtual control that makes the system stabile is obtained. The system stability is guaranteed by the Lyapunov stability theory. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.633-635
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• 1997

In this paper we present a scheme of adaptive backstepping controller for nonlinear system. Backstepping approach has recently been adopted as a design tool for nonlinear control and especially backstepping with modular design used to seperately design controller and identifier. In the modular design the nonlinear damping term is contained in controller for input-to-state stability (ISS). We compare the ISS controller, which used in general case, with the weak-ISS controller that attenuates the effect of nonlinear damping term and prove their advantages and disadvantages by simulation.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.324-326
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• 2006

This paper present backstepping control approach for controling chaotic Liu system. The proposed method is a systematic design approach and consists in a recursive procedure that interlaces the choice of a Lyapunov Function. Based on Lyapunov stability theory, control laws are derived. We used the same technique to enable stabilization of chaotic motion to a steady state as well as tracking of any desired trajectory to be achieved in a systematic way. Numerical solution are shown to verify the result.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.4
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• pp.211-216
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• 2005

In this paper a robust controller using adaptive backstepping technique is proposed to control the speed of wind power generation system. To make wind power generation truly cost effective and reliable, advanced and robust control algorithms are derived to on-line adjust the excitation winding voltage of the generator based on both mechanical and electrical dynamics. This method is shown to be able to achieve smooth and asymptotic rotor speed tracking, as justified by analysis and computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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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 ...