• 한국통신학회논문지
• /
• 제22권4호
• /
• pp.696-705
• /
• 1997

This paper presents an efficient adaptive predistortion technique compensating linear and nonlinear distortions caused by high-power amplifier (HPA) with memory in OFDM systems. The efficient adaptive data predistortion techniques proposed for compensation of HPA with memory in single carrier systems cannot be applied to OFDM systems since the possible input levels for HPA is infinite in OFDM systems. Also, previous adaptive predistortion techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In the proposed approach, the memoryless HPA preceded by a linear filter in OFDM systems is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. An adaptive algorithm for adjusting the proposed adaptive predistorter is derived using the stochastic gradient method. It is demonstrated by computer simulation that the performance of OFDM system suffering from nonlinear distortion can be greatly improved by the proposed efficient adaptive predistorter using a small number of filter taps.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제1권1호
• /
• pp.29-34
• /
• 2001

This paper is devoted to investigating direct adaptive neural control of nonlinear systems with uncertain or unknown dynamic models. In the direct adaptive neural networks control area, theoretical issues of the existing backpropagation-based adaptive neural networks control schemes. The major contribution is proposing the variable index control approach, which is of great significance in the control field, and applying it to derive new stable robust adaptive neural network control schemes. This new schemes possess inherent robustness to system model uncertainty, which is not required to satisfy any matching condition. To demonstrate the feasibility of the proposed leaning algorithms and direct adaptive neural networks control schemes, intensive computer simulations were conducted based on the flexible joint robot systems and functions.

• 한국정밀공학회지
• /
• 제14권2호
• /
• pp.152-159
• /
• 1997

The asymptotic convergence of a coupled dynamic system, which is motivated from infinite dimensional adaptive systems, is investigated. The convergence analysis is formulated in abstract Banch spaces and is shown to applicable to a broad class of infinite dimensional systems including adaptive identification and adaptive control. Particularly it is shown that if a uniquely existing solution is p-th power integrable, then the solution converges to zero asymptotically. The persistence of excitation(PE) of a signal which arises in an infinite dimensional adaptive system is investigated. The PE property is not completely known yet for infinite dimensional adaptive systems, however it should be investigated in relation to spatial variable, boundary conditions as well as time variable.

• 디지털콘텐츠학회 논문지
• /
• 제12권3호
• /
• pp.355-360
• /
• 2011

본 논문에서 OFDM 시스템의 성능분석을 Matlab 시뮬레이터를 이용하여 시뮬레이션 하였다. 적응 OFDM 시스템에 채널 추정 알고리즘을 적용하고 멀티미디어 무선통신 다중경로 페이딩 채널환경에서 시스템에 미치는 영향을 분석하고 추정된 결과를 이용하여 적응 등화기를 적용한 적응 OFDM 시스템의 성능을 BER을 통하여 분석하였다. 분석결과, 채널상태에 따라 가변을 취하는 적응변조 OFDM 시스템의 경우 일반적인 시스템에 비해 (BER=$10^{-1}$)를 기준으로 약 7dB 성능의 이득이 있음을 확인하였다. 따라서 고속 멀티미디어 무선통신 채널환경에서 효율적인 전송을 위해 제안한 적응 시스템이 효율적임을 확인 하였다.

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

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.941-946
• /
• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• 제어로봇시스템학회논문지
• /
• 제15권6호
• /
• pp.598-603
• /
• 2009

The checkpointing scheme is a well-known technique to cope with transient faults in digital systems. This paper proposes an adaptive checkpointing scheme for the reliability improvement of real-time control systems. The proposed adaptive checkpointing scheme is based on the previous work about the reliability problem of an equidistant checkpointing scheme. For the derivation of the adaptive scheme, some conditions are introduced which are to be satisfied for the reliability improvement by exploiting an equidistant checkpointing scheme. Numerical data show the proposed adaptive scheme outperforms the equidistant scheme from a reliability point of view.

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

• International Journal of Control, Automation, and Systems
• /
• 제1권1호
• /
• pp.19-27
• /
• 2003

It is well known that one can easily design a high-gain adaptive output feedback control for a class of nonlinear systems which satisfy a certain condition called output feedback exponential passivity (OFEP). The designed high-gain adaptive controller has simple structure and high robustness with regard to bounded disturbances and unknown order of the controlled system. However, from the viewpoint of practical application, it is important to consider a robust control scheme for controlled systems for which some of the assumptions of output feedback stabilization are not valid. In this paper, we design a robust high-gain adaptive output feedback control for the OFEP nonlinear systems with uncertain nonlinearities and/or disturbances. The effectiveness of the proposed method is shown by numerical simulations.

• International Journal of Aeronautical and Space Sciences
• /
• 제12권4호
• /
• pp.360-364
• /
• 2011

Backlash is common in mechanical and hydraulic systems and severely limits overall system performance. In this paper, the development of an adaptive control scheme for systems with unknown backlash is presented. An adaptive backlash inverse based controller is applied to a plant that has an unknown backlash in its input. The harmful effects of backlash are presented. Compensation for backlash by adding a discrete adaptive backlash inverse structure and the gradient-type adaptive algorithm, which provides the estimated backlash parameters, are also presented. The supposed adaptive backlash control algorithms are applied to an aircraft with unknown backlash in the actuator of control surfaces. Simulation results show that the proposed compensation scheme improves the tracking performance of systems with backlash.