• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.187-190
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• 2003

In this paper, we address the robust adaptive backstepping controller using fuzzy neural network (FHIN) for a class of uncertain output feedback nonlinear systems with disturbance. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The state estimation is solved using K-fillers. All unknown nonlinear functions are approximated by FNN. The FNN weight adaptation rule is derived from Lyapunov stability analysis and guarantees that the adapted weight error and tracking error are bounded. The compensated controller is designed to compensate the FNN approximation error and external disturbance. Finally, simulation results show that the proposed controller can achieve favorable tracking performance and robustness with regard to unknown function and external disturbance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1592-1598
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• 2011

In this paper, a formation control method based on the leader-following approach for nonholonomic mobile robots is proposed. In the previous works, it is assumed that the followers know the leader's velocity by means of communication. However, it is difficult that the followers correctly know the leader's velocity due to the contamination or delay of information. Thus, in this paper, an adaptive approach based on the parameter projection algorithm is proposed to estimate the leader's velocity. Moreover, the adaptive backstepping technique is used to compensate the effects of a dynamic model with the unknown time-invariant and time-varying parameters. From the Lyapunov stability theory, it is proved that the errors of the closed-loop system are uniformly ultimately bounded. Simulation results illustrate the effectiveness of the proposed control method.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.292-300
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• 2009

This paper considers a robust adaptive stabilization problem for a class of uncertain nonlinear systems which include an unknown virtual control coefficient, an unknown constant parameter, and a time-varying disturbance whose bound is unknown, We propose a new estimator for an un-known virtual control coefficient and present a robust adaptive backstepping design procedure which results in a smooth state feedback control law, a new two-dimensional parameter update law, and a $C^1$ Lyapunov function which is positive definite and proper.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1646_1647
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• 2009

In this paper, Takagi-Sugeno(T-S) fuzzy controller and search method are developed for efficiency optimization of induction motors(IMs). The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of T-S fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is used to control of speed of IMs. Simulation results are presented to validate the proposed controller.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2711-2713
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• 2005

This paper presents the tracking control method of robotic systems with uncertainties using self recurrent wavelet neural network (SRWNN) via the backstepping design technique. The SRWNN is used as the uncertainty observer of the robotic systems. The adaptation laws for weights of the robotic systems are induced from the Lyapunov stability theorem, which are used for on-line controlling robotic systems. Computer simulations of a three-link robot manipulator with uncertainties verify the validity of the proposed SRWNN controller.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.327-329
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• 2006

A controller is proposed for the robust adaptive backstepping control of a class of uncertain nonlinear systems using nonlinear disturbance observer (NDO). The NDO is applied to estimate the time-varying lumped disturbance in each step, but a disturbance observer error does not converge to zero since the derivative of lumped disturbance is not zero. Then the fuzzy neural network (FNN) is presented to estimate the disturbance observer error such that the outputs of the system are proved to converge to a small neighborhood of the desired trajectory. The proposed control scheme guarantees that all the signals in the closed-loop are semiglobally uniformly ultimately bounded on the basis of the Lyapunov theorem. Simulation results are presented to illustrate the effectiveness and the applicability of the approaches proposed.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.270-277
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• 2005

In this paper, a decentralized control problem is considered for multimachine power systems with nonlinear interconnections and disturbances. A direct feedback linearization compensator is employed to cancel most of the nonlinearities, and then a backstepping procedure is applied to deal with the interconnections and to reduce the effects of a disturbance that does not satisfy the matching condition. In this procedure, the disturbance is handled by using a smooth approximation of the signum function. Practical stability is achieved under the assumption that the infinite norm of the disturbance is known. However, even in the case where the infinite norm of the disturbance is not known precisely, the proposed control system still guarantees $L_2$ stability. Furthermore, the origin is globally uniformly asymptotically stable in the absence of the disturbance. A three-machine power system is considered as an application example.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.278-287
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• 2005

In this paper a new excitation control scheme that improves the transient stability of multi machine power systems is proposed. To this end the backstepping technique is used to transform the system to a suitable partially linear form. On this system, a combination of both feedback linearization and adaptive control techniques are used to confront the nonlinearities. As shown in the paper, the resulting nonlinear control law ensures the uniform boundedness of all the state and estimated variables. Furthermore, it is proven that all the error variables are uniformly ultimately bounded (DUB) i.e. they converge to arbitrarily selected small regions around zero in finite-time. Simulation tests on a two generator infinite bus power system demonstrate the effectiveness of the proposed control.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.74-76
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• 2009

In this paper, search method and sliding mode observer are developed for efficiency optimization of induction motor. The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. The search controller is based on the "Rosenbrock" method and finds the flux level at the minimum input power of induction motor. Once this optimal flux level has been determined, this information is utilized to update the rule base of a fuzzy controller A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is also used to compensate for mechanical uncertainties in the speed control of induction motor. Simulation results are presented to validate the proposed controller.

• Journal of Ocean Engineering and Technology
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• v.16 no.4
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• pp.54-60
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• 2002

본 연구는 슬라이딩 모드개념을 이용한 비선형 견실 상태 추정기의 선박 위치제어시스템에 대한 적용에 관한 연구이다. 개발된 상태추정기는 제어기 설계에 필요한 동적 모델에 있어서 고려되지 않은 비선형성과 불확실성 및 외란이 존재하더라도 견실히 상태추정을 수행할 수 있는 장점을 가지고 있다. 또한 선박의 속도 및 유체력으로 인한 외란의 추정이 가능하며, 파랑으로 인한 고주파 운동응답을 여과시킴으로 불필요한 작동기의 동작과 과도한 연료손실을 방지할 수 있다. 특히 상태 추정기에 불연속 함수를 도입함으로 비선형성, 외란 및 불확실성에 대해 강인한 특성을 가지고 있다. 제안된 상태추정기에 기초하여 Observer backstepping 방법을 이용한 위치 제어기가 설계되었으며, 제어시스템의 안정성을 Lyapunov 법을 이용하여 검증하였다. 일련의 수치 시뮬레이션을 수행함으로서 제안된 상태추정기 및 제어기의 선박위치제어시스템으로서의 성능을 예증하였다.