• Kyungpook Mathematical Journal
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• 제54권2호
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• pp.293-320
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• 2014

In this paper, global chaos synchronization is investigated for WINDMI (J. C. Sprott, 2003) and Coullet (P. Coullet et al, 1979) chaotic systems using adaptive backstepping control design based on recursive feedback control. Our theorems on synchronization for WINDMI and Coullet chaotic systems are established using Lyapunov stability theory. The adaptive backstepping control links the choice of Lyapunov function with the design of a controller and guarantees global stability performance of strict-feedback chaotic systems. The adaptive backstepping control maintains the parameter vector at a predetermined desired value. The adaptive backstepping control method is effective and convenient to synchronize and estimate the parameters of the chaotic systems. Mainly, this technique gives the flexibility to construct a control law and estimate the parameter values. Numerical simulations are also given to illustrate and validate the synchronization results derived in this paper.

• 제어로봇시스템학회논문지
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• 제20권10호
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• pp.1002-1007
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• 2014

This paper deals with the adaptive backstepping hovering control for a quadrotor with model parameter uncertainties. In this paper, the backstepping based technique is utilized to design a nonlinear adaptive controller which can compensate for the motor thrust factor and the drag coefficient of a quadrotor. First, the quadrotor nonlinear dynamics is derived using Newton-Euler formulation. In particular, we use the ${\pi}/4$ shifted coordinate for x- and y-axis of a quadrotor. Second, an adaptive backstepping based attitude and altitude tracking control method is presented. The system stability and the convergence of tracking errors are proven using the Lyapunov stability theory. Finally, the simulation results are given to verify the effectiveness of the proposed control method.

• 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.

• 전기학회논문지P
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• 제54권4호
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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.

• 한국정밀공학회지
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• 제23권7호
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• pp.24-29
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• 2006

• 전자공학회논문지SC
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• 제41권4호
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• pp.1-12
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• 2004

본 논문에서는 적응 퍼지 백스테핑 알고리즘을 이용하여 단일축 유연관절 로봇을 제어하는 새로운 알고리즘을 제안한다. 퍼지시스템은 일반근사기로 사용하여 로봇과 제어기의 비선형성과 불확실성을 상쇄하는 역할을 한다. 제안한 알고리즘은 추가적인 교시 제어기를 필요로 하지 않으며 추적오차를 상시유계시키는 특성이 있다. 끝으로 컴퓨터 모의실험을 통하여 제안한 방식의 성능을 확인한다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2010년도 하계학술대회 논문집
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• pp.606-607
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• 2010

본 논문은 CVCF 인버터 출력전압을 정현파로 제어하는 기법을 제안한다. 왜곡이 없는 깨끗한 정현파 출력전압을 요구하는 AVR이나 UPS에 적용이 가능하다. 변동 부하나 비선형 부하에 대해서도 출력을 안정되게 제어할 수 있는 장점이 있다. Backstepping 제어 기법을 이용하여 인버터 출력전류를 가상 제어변수로 선정하고 콘덴서 양단전압이 지령값을 추종하도록 가상 제어변수를 조절하고 이를 위해 인버터 출력전압인 입력 제어변수를 조절한다. 출력 필터의 L값의 변동을 고려하여 Adaptive parameter 보상 알고리즘을 적용하여 정밀한 Parameter값을 요구하는 Backstepping 기법의 단점을 보완하였다. 제안한 알고리즘의 타당성을 시뮬레이션을 통해 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.48.1-48
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• 2001

In this paper, we present a global adaptive output feedback control scheme for a class of uncertain nonlinear systems to which adaptive observer backstepping method may not be applicable directly. The allowed output feedback structure includes quadratic and multiplicative dependency of unmeasured states. Our novel design technique employs a change of coordinates and adaptive backstepping. With these proposed tools, we can remove linear and quadratic dependence on the unmeasured states in the state equation. Also, the multiplication of the two unmeasured states can be eliminated ...

• 드라이브 ㆍ 컨트롤
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• 제19권1호
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• pp.51-61
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• 2022

This paper presents a model-free system based on a framework of a backstepping sliding mode control (BSMC) with a radial basis function neural network (RBFNN) and adaptive mechanism for electro-hydraulic systems (EHSs). First, an EHS mathematical model was dedicatedly derived to understand the system behavior. Based on the system structure, BSMC was employed to satisfy the output performance. Due to the highly nonlinear characteristics and the presence of parametric uncertainties, a model-free approximator based on an RBFNN was developed to compensate for the EHS dynamics, thus addressing the difficulty in the requirement of system information. Adaptive laws based on the actor-critic neural network (ACNN) were implemented to suppress the existing error in the approximation and satisfy system qualification. The stability of the closed-loop system was theoretically proven by the Lyapunov function. To evaluate the effectiveness of the proposed algorithm, proportional-integrated-derivative (PID) and improved PID with ACNN (ACPID), which are considered two complete model-free methods, and adaptive backstepping sliding mode control, considered an ideal model-based method with the same adaptive laws, were used as two benchmark control strategies in a comparative simulation. The simulated results validated the superiority of the proposed algorithm in achieving nearly the same performance as the ideal adaptive BSMC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.77-78
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• 2008

This paper presents to control speed of induction motors with uncertainties. We use an adaptive backstepping controller with fuzzy neural networks(FNNs) and model reference adaptive system(MRAS) at Indirect vector control method. The adaptive backstepping controller using FNNs can control speed of induction motors even we have a minimum of information. And this controller can be used to approximate most of uncertainties which are derived from unknown motor parameters, load torque such as disturbances. MRAS estimates to rotor resistance and also can find optimal flux to minimize power losses of Induction motor. Indirect vector PI current controller is used to keep rotor flux constant without measuring or estimating the rotor flux. Simulation and experiment results are verified the effectiveness of this proposed approach.