• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.15-22
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• 2009

The guidance controller of the conventional aircraft consists of inner-loop (autopilot) and outer-loop (guidance). If the guidance controller can be designed as an integrated guidance and control (IGC), the various advantages exist. The integrated guidance and control formulation can compensate for the effect of autopilot lag. An integrated approach also helps avoid the iterative procedure involved in tuning the guidance and autopilot subsystems, if designed separately. Integrated design is also less susceptible to saturation and stability problems. This paper presents an approach to IGC design for the unpowered air vehicle with the only flaperon using a combination of adaptive output feedback inversion and backstepping techniques. Adaptive neural networks are trained online with available measurements to compensate for unmodeled nonlinearities in the design process.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2006년도 전력전자학술대회 논문집
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• pp.523-525
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• 2006

Adaptive neural state-feedback controllers for the fully nonaffine pure-feedback nonlinear system are presented in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controllers require no backstepping design procedures. Avoiding backstepping makes the controller structure and stability analysis considerably to be simplified. The proposed controllers employ only one neural network to approximate unknown ideal controllers, which highlights the simplicity of the proposed neural controller.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권10호
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• pp.563-571
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• 2000

In this paper, a nonlinear adaptive control method for an EMS(Electro-Magnetic Suspension) system with mass uncertainty is proposed. Using the coordinate transformation and feedback linearizing control, EMS system has been transformed into the form of parametric strict-feedback system with unknown virtual control coefficients. With this transformed system, tuning functions approach, which is an advanced from of adaptive backstepping, has been applied in order to stabilize the system against mass uncertainty. Computer simulation is also carried out in order to compare the performance of the proposed controller with that of feedback linerizing controller.

• 전기학회논문지
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• 제58권9호
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.

• 전자공학회논문지SC
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• 제47권2호
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• pp.16-24
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• 2010

본 논문은 불특정한 외란을 가진 비선형 시스템에서의 백스태핑 기법을 이용한 새로운 퍼지 외란 관측가 설계 방법을 제안한다. 먼저, 퍼지 논리 시스템을 이용하여 불특정한 외란을 관측하기 위한 관측 입력을 가진 퍼지 외란 관측기를 설계한다. 제안된 외란 관측기가 불특정한 외란을 관측하는 것을 증명하기 위해 와란 관측 오차 시스템을 도입한다. 백스태핑 기법을 도입하여 각 단계에서의 퍼지 외란 관측기의 파라마터 적응 규칙과 외란 관측기의 관측 입력을 유도하고 외란 오차 시스템의 안정성을 증명한다. 제안된 외란 관측기의 명확성을 증명하기 위해서 모의 실험 예제들을 제공한다.

• 한국정밀공학회지
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• 제34권2호
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• pp.125-131
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• 2017

2-Axis Pan and Tilt Motion Platform, a complex multivariate non-linear system, may incur any disturbance, thus requiring system controller with robustness against various disturbances. In this study, we designed an adaptive backstepping compensated controller by estimating the disturbance and error using the Radial Basis Function Neural Network (RBF NN). In this process, Uniformly Ultimately Bounded (UUB) was demonstrated via Lyapunov and stability was confirmed. By generating progressive disturbance to the irregular frequency and amplitude changes, it was verified for various environmental disturbances. In addition, by setting the RBF NN input vector to the minimum, the estimated disturbance compensation process was analyzed. Only two input vectors facilitated compensatory function of RBF NN via estimating the modeling and control error values as well as irregular disturbance; the application of the process resulted in improved backstepping controller performance that was confirmed through simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.779-781
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• 1999

In this paper we consider the TORA system and use backstepping to design active controllers for tracking; this problem is much more challenging than stabilization. We show that the control effort of the closed-loop system can be significantly improved by exploiting the backstepping design.

• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.588-591
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• 1998

In this paper, we present a robust adaptive backstepping output feedback controller for nonlinear systems perturbed by unmodelled dynamics and disturbances. Especially, backstepping technique with modular approach is used to separately design controller and identifier. The design of identifier is based on the observer-based scheme which possesses a strict passivity property of observer error system. We will use Switching-${\sigma}$ modification at the update law and the modified control law to attenuate the effects of undodelled dynamics and disturbances for nonlinear systems.

• 전기학회논문지P
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• 제56권1호
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• pp.6-12
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• 2007

In this paper, an robust adaptive backstepping controller is proposed for the speed control of separately excited DC motor in pure electric vehicles. A general electric drive train of PEV is conceptually rearrange to major subsystems as electric propulsion, energy source, and auxiliary subsystem and the load torque is modeled by considering the aerodynamic, rolling resistance and grading resistance. Armature and field resistance, damping coefficient and load torque are considered as uncertainties and noise generated at applying load torque to motor is also considered. It shows that the backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the proposed controller.