• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2224-2226
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• 2003

서보시스템은 공작 기계, 자동화기계용 등의 제어에 사용되고 있는 대표적인 제어 시스템으로서 관성 디스크를 교환하기도 하며 전자가변 포화도와 히스테리시스등을 사용하여 고정밀 연구용에도 이용가능하다. 그러나 모델의 불확실성이나 외부외란이 필연적으로 존재할 수 밖에 없으므로 이를 분석하고 규명하여 원하는 목적의 제어를 위한 제어기를 설계해야만 할 것이다. 따라서, 본 연구에서는 제어대상 시스템의 불화실성을 극복할 수 있고 비선형항의 소거를 통한 선형화가 아닌 비선형 제어기의 설계를 가능하게 하는 Backstepping 제어기법을 사용하여 서보시스템의 정밀한 제어와 시스템 안정성을 보장하고자 한다. Backstepping 제어기를 설계하여 다양한 조건하에서의 시뮬레이션을 수행하여 제안하는 제어기의 최적 수행 능력을 보이고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.405-413
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• 2006

In general mechanical servo systems, friction deteriorates the performance of controllers by its nonlinear characteristics. Especially, friction phenomenon causes steady-state tracking errors and limit cycles in position and velocity control systems, even though gains of controllers are tuned well in linear system model. Even if sensor is used higher accuracy level, it is difficult to improve tracking performance of the position to the same level with a general control method such as PID type. Therefore, many friction models were proposed and compensation methods have been researched actively. In this paper, we consider that the variation of mover's mass is various by loading and unloading. The normal force variation occurs by it an other parameters. Therefore, the proposed control system is composed of main position controller and a friction compensator. A parameter estimator for a nonlinear friction model is designed by adaptive control law and adaptive backstepping control method.

• Journal of Navigation and Port Research
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• v.31 no.1 s.117
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• pp.55-64
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• 2007

In general mechanical servo systems, friction deteriorates the performance of controllers by its nonlinear characteristics. Especially, friction phenomenon causes steady-state tracking errors and limit cycles in position and velocity control systems, even though gains of controllers are tuned well in linear system model. Even if sensor is used higher accuracy level, it is difficult to improve tracking performance of the position to the same level with a general control method such as PID type. Therefore, many friction models were proposed and compensation methods have been researched actively. In this paper, we consider that the variation of mover's mass is various by loading and unloading. The normal force variation occurs by it and other parameters. Therefore, the proposed control system is composed of main position controller and a friction compensator. A parameter estimator for a nonlinear friction model is designed by adaptive control law and adaptive backstepping control method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.583-586
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• 2013

We consider discrete-time LTI (Linear Time-Invariant) systems with constant input delays. The input delay is modeled by a first-order PdE (Partial difference Equation) and a backstepping transformation is employed to design a predictor feedback controller. The backstepping approach results in the construction of an explicit Lyapunov function, with which we prove the exponential stability of the closed-loop system formed by the predictor feedback. The numerical example demonstrates the design of the predictor feedback controller, and illustrates the validity of the exponential stability.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2138-2139
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• 2002

In this paper we presents a speed controller for separately excited DC motor using adaptive backstepping technique. The motor was modeled in two local areas the first model is a linear one when speed is under base speed, the other is nonlinear one when field weakening is used to obtain the speed well above base speed. Then linear robust state feedback controller was designed for the linear model while adaptive backstepping controller was designed for the nonlinear model. The adaptive backstepping technique takes system nonlinearity into account in the control system design stage. The proposed controller is proved to be asymptotically stable by the Lyapunov stability theory and some simulations have been carried out to test.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.128-131
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• 2005

In this paper a robust controller using adaptive backstepping technique is proposed to control the speed of a wind turbine 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 position tracking, as justified by analysis.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1227-1229
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• 2007

In this paper a robust controller using adaptive backstepping technique is proposed to control the position 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.

• Journal of IKEEE
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• v.14 no.3
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• pp.182-189
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• 2010

A new Adaptive neural state-feedback controller 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 controller requires no backstepping design procedure. Avoiding backstepping makes the controller structure and stability analysis considerably simple. The proposed controller employs only one neural network to approximate unknown ideal controllers, which highlights the simplicity of the proposed neural controller. Simulation examples demonstrate the efficiency and performance of the proposed approach.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.5
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• pp.817-832
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• 2015

This paper presents a state feedback based backstepping control algorithm to address the trajectory tracking problem of an underactuated Unmanned Surface Vessel (USV) in the horizontal plane. A nonlinear three Degree of Freedom (DOF) underactuated dynamic model for USV is considered, and trajectory tracking controller that can track both curve trajectory and straight line trajectory with high accuracy is designed as the well known Persistent Exciting (PE) conditions of yaw velocity is completely relaxed in our study. The proposed controller has further been enriched by incorporating an integral action additionally for enhancing the steady state performance and control precision of the USV trajectory tracking control system. Global stability of the overall system is proved by Lyapunov theory and Barbalat's Lemma, and then simulation experiments are carried out to demonstrate the effectiveness of the controller designed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.