• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.26-30
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• 1995

In this study, the fuzzy approximator and sliding mode control (SMC) scheme are considered. An adaptive sliding mode control is proposed based on the SMC theory. This proposed control scheme is that a adaptive law is utilized to approximate the unknown function f by fuzzy logic system in designing the sliding mode controller for the nonlinear system. In order to reduce the approximation errors, the differences of nonlinear function and fuzzy approximator, an adaptive law is also intoduced and the stability of proposed control scheme are proven with simple adaptive law and roburst adaptive law. This proposed control scheme is applied to a single link robot arm.

• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.680-688
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• 2004

This paper proposes an observer-based method for adaptive nonlinear guidance. Previously, adaptive nonlinear guidance law is proposed considering target maneuver and control loop dynamics. However, several information of this guidance law is not available, and therefore needs to be estimated for more practical application. Accordingly, considering the unavailable information as bounded time-varying uncertainties, an integrated guidance and control model is re-formulated in normal form with respect to available states including target uncertainties and control loop dynamics. Then, a nonlinear observer is designed based on the integrated guidance and control model. Finally, using the estimates for states and uncertainties, an observer-based adaptive guidance law is proposed to guarantee the desired interception performance against maneuvering target. The proposed approach can be effectively used against target maneuver and the limited performance of control loop. The stability analyses and simulations of the proposed observer and guidance law are included to demonstrate the practical application of our scheme.

• 대한전자공학회논문지
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• 제26권8호
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• pp.1167-1177
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• 1989

In this paper, a generalized adaptive law is proposed which uses a rational function type operator for parameter adjustment. To satisfy the passivity condition of the adaptation block, we introduce a constant feedback gain into the adaptation block. This adaptation scheme is applied to the model reference adaptive control of a continuous-time, linear time-invariant, minimum-phase system whose relative degree is 1. We prove the asymptotic stability of the output error of this adaptive system by hyperstability method. It is shown that by digital computer simulations this law can give a better output error transient response in some cases than the conventional gradient adaptive law. And the output error responses for the several types of the proposed adaptation law are examined in the presence of a kind of unmodeled dynamics.

• 제어로봇시스템학회논문지
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• 제2권2호
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• pp.67-72
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• 1996

This paper presents a parameter adaptive control law that stabilizes and asymptotically regulates any single-input, linear time-invariant, controllable and observable, discrete-time system when only the upper bounds on the order of the system is given. The algorithm presented in this paper comprises basically a nonlinear state feedback law which is represented by functions of the state vector in the controllable subspace of the model, an adaptive identifier of plant parameters which uses inputs and outputs of a certain length, and an adaptive law for feedback gain adjustment. A new psedu-inverse algorithm is used for the adaptive feedback gain adjustment rather than a least-square algorithm. The proposed feedback law results in not only uniform boundedness of the state vector to zero. The superiority of the proposed algorithm over other algorithms is shown through some examples.

• 대한전기학회논문지
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• 제35권12호
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• pp.573-578
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• 1986

The adaptive control of a plant in the presence of disturbance is considered. In sevral papers, it was shown that bounded disturbance made the basic adaptive scheme unstable. For achieving robust stability in adaptive control system in the presence of disturbance, the pureintegration in the adaptive law is limited by means of an additional feedback term. In this paper, the suggested adaptive control law has property that the output error converges to zero whether the disturbance exist or not, without the priori knowledge. The adaptive controller suggested assure the boundness of all signal in the overall system. Finally, computer simulation show the effectiveness of the suggested adaptive control law.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.519-524
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• 2003

In this report, a longitudinal adaptive flight control law is presented for the automatic landing system of a Japanese automatic landing flight experiment vehicle (ALFLEX). The longitudinal adaptive flight control law is designed to track an output of the vehicle to a guidance signal from the guidance portion of the automatic landing system. The proposed adaptive control law in the attitude control portion adjusts the controller gains continuously online as flight conditions change, in spite of the existence of unmodeled dynamics. The number of the controller gains to be adjusted is decreased to 1/2 from the previous studies. Computer simulation involving six-degree-of-freedom (DOF) nonlinear flight dynamics is performed to examine the effectiveness of the proposed adaptive control law. In order to verify the influence of the dispersion of the initial conditions, the Monte Carlo simulation is also applied. The initial conditions are more widely dispersed than the previous studies. As a result, except under the unsuitable initial conditions, the ALFLEX successfully landed on the runway.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.148.5-148
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• 2001

In this report, an adaptive flight control law based on a linear-parameter-varying (LPV) model is presented for a flight control system. The control system is designed to track an output of a vehicle to a reference signal from the guidance system, which generates a reference flight path. The proposed adaptive control law adjusts the controller gains continuously on line as flight conditions change. The obtained adaptive controller guarantees global stability over a wide flight envelope. Computer simulation involving six-degree-of-freedom nonlinear flight dynamics is applied to Japan´s automatic landing flight experimental vehicle (ALFLEX) to examine the effectiveness of the proposed adaptive flight control law.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.2-2
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• 2000

This paper presents an adaptive control against uncertainties in tail-controlled STT (skid-to-Turn) missiles. First, we derive an analytic uncertainty model from a parametricaffine missile model developed by the authors. Based on this analytic model, an adaptive feedbacklinearizing control law accompanied by a sliding model control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme is demonstrated by simulation.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• 한국생산제조학회지
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• 제19권2호
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• pp.241-250
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• 2010

A recurrent adaptive model-free intelligent control with a friction estimation law is proposed to enhance the positioning performance of the mover in PMLSM system. For the PMLSM with nonlinear friction and uncertainty, an adaptive recurrent fuzzy neural network(ARFNN) and compensated control law in $H_{\infty}$ performance criterion are designed to mimic a perfect control law and compensate the approximated error between ideal controller and ARFNN. Combined with friction observer to estimate nonlinear friction parameters of the LuGre model, on-line adaptive laws of the controller and observer are derived based on the Lyapunov stability criterion. To analyze the effectiveness our control scheme, some simulations for the PMLSM with nonlinear friction and uncertainty were executed.