• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1844-1851
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• 2007

This paper presents methods for the compensation of sinusoidal disturbances with unknown amplitude, phase, and time-varying frequency in nonlinear systems. In the previous disturbance accommodation methods, the sinusoidal disturbance with unknown time-invariant frequency was considered. In the proposed method, the disturbance with unknown time-varying frequency is compensated. As for the control structure, two control inputs are designed separately in such a way that one of them is designed for the nonlinear system control without considering the disturbance, and the other one uses the disturbance estimate obtained from the disturbance accommodating observer. The stability analysis is done considering the disturbance estimation error and the numerical simulation demonstrates the proposed approach.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.991-1000
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• 1994

To control nonlinear systems adaptively, we improve learning speed of neural networks and present a novel control algorithm characterized by compensation of control inputs. In an error-backpropagation algorithm for tranining multilayer neural networks(MLNN's) the effect of the slope of activation functions on learning performance is investigated and the learning speed of neural networks is improved by auto-adjusting the slope of activation functions. The control system is composed of two MLNN's, one for control and the other for identification, with the weights initialized by off-line training. The control algoritm is modified by a control strategy which compensates the control error induced by the indentification error. Computer simulations show that the proposed control algorithm is efficient in controlling a nonlinear system with abruptly changing parameters.

• Journal of Ocean Engineering and Technology
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• v.13 no.3B
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• pp.99-105
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• 1999

In order to reject the steady-state tracking error, it is common to introduce integral compensators in servosystems for constant reference signals. However, if the mathematical model of the plant is exact and no disturbance input exists, the integral compensation is not necessary. From this point of view, a two-degree-of-freedom(2DOF) servosystem has been proposed, in which the integral compensation is effective only when there is a modeling error or a disturbance input. The present paper considers a robust stability of this 2DOF servosystem with nonlinear type uncertainty in the system, and a robust stability condition for the servosystem is introduced. This result guarantees that if the plant uncertainty is in the permissible set defined by the condition, gain tuning can be carried out to suppress the influence of the plant uncertainties and disturbance inputs.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.567-574
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• 2006

This paper presents the hardware implementation of a neural network controller for a nonlinear system with a micro-controller unit (MCU) and a field programmable gate array (FPGA) chip. As an on-line learning algorithm of a neural network, the reference compensation technique has been implemented on an MCU, while PID controllers with other functions such as counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The developed neural control hardware has been tested for balancing the inverted pendulum while controlling a desired trajectory of a cart as a nonlinear system.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.302-307
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• 2006

The aim of applying Functional Electrical Stimulation (FES) is to restore a person's motor function by directly supplying the controlled electrical currents to the site of the paralyzed muscles. However, most clinically utilized FES systems have adapted an open-loop control scheme. Recently the closed-loop control scheme has been considered for setting up the FES system, but due to the inherent nonlinearities in the musculoskeletal system, the nonlinearities were not fully compensated and it caused the oscillatory responses for tracking the output variables. In this study, a nonlinear controller model that has two inverse compensation units is proposed with the compromising feedback linearization method and this will eventually be used to design the FES control system for stimulating a knee joint musculoskeletal system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.27-36
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• 2012

We propose a new scheme combining the calibration of the path imperfections and the compensation of HPA nonlinearity in the downlink OFDM smart antenna systems. We use a two term third-order polynomial (without second-order term) and the indirect learning architecture for calibration and compensation, to make each path of the antenna array have equal characteristics. We test our scheme with computer simulations. The result shows that, with the addition of only one third-order term, the adverse nonlinear effects as well as the those of linear imperfections can be effectively compensated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.197-204
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• 2012

We propose a new scheme combining the compensation of HPA nonlinearity and the calibration of the path imperfections in the downlink OFDM smart antenna systems. We use a two term third-order polynomial (without second-order term) and the feedforward method for compensation and calibration to make each path of the antenna array have equal characteristics. Since the proposed scheme does not alter the base-band signal, it can be applied to the smart antenna system independently of the base-band signal processing section. The result of computer simulations shows that, with the addition of only one third-order term, the adverse nonlinear effects can be effectively compensated, and the those of linear imperfections can be calibrated as well.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.939-942
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• 1989

Most of systems are included nonlinear characteristics in practice. One might be faced with difficulties when problems of nonlinear systems are solved. In this paper we present a formal linearization method of nonlinear systems by using the trigonometric Fourier expansion on the state space considering easy inversion. An error bound, an application, and a compensation of this method are also investigated.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.534-534
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• 2000

This paper proposes a dynamic compensation scheme for input-constrained feedback linearizable nonlinear systems to cope with the windup phenomenon. Given a feedback linearizing controller for such a nonlinear system designed without considering its input constraint, an additional dynamic compensator is proposed to account for the constraint. This dynamic anti-windup is based on the minimization of a reasonable performance index, and some stability properties of the resulting closed-loop are presented.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.583-595
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• 2008

In this paper, we introduce a fuzzy nonlinear feedback approach to the control of a class of chaotic dynamical systems. The fuzzy Parallel Distributed Compensation with Reduced Rule Base approach (PDC_RRB) is proposed. The design procedure is conceptually simple and considered to a nonlinear optimal and robust control problem due to the nonlinear nature of the Takagi-Sugeno (TS) fuzzy system. Simulation results are provided to show the effictiveness of the proposed methodology.