• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.636-639
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• 1997

In this paper, a dynamic control scheme is proposed which not only compensates for the lateral dynamics and longitudinal dynamics but also deal with the yaw motion dynamics. Using the dynamic control technique, adaptive and learning algorithm together, the proposed controller is not only robust to disturbance and parameter uncertainties but also can learn the inverse dynamics model in steady state. Based on the proposed dynamic control scheme, a dynamic vehicle simulator is contructed to design and test various control techniques for 4-wheel steering vehicles.

• Journal of the Korean Mathematical Society
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• v.49 no.6
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• pp.1175-1196
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• 2012

A class of autonomous control systems with fixed unknown parameters is considered to be stabilized with respect to only a part of the variables. A certain type of such systems can be recursively adaptively partially stabilized. The bifurcation analysis reveals the nature of the closed loop system.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.84-86
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• 2005

Adaptive tracking, disturbance rejection and power system stabilizer. First, this paper deals with power system stabilization problem using asymptotic tracking of arbitrary smooth bounded reference output signals, with simultaneous rejection of disturbances generated by an unknown linear exosystem. Second, this paper presents a power system stabilizer(PSS) using nonlinear adaptive observer backstepping controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.706-709
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• 2005

We study the adaptive stabilization of the Van der Pol equation. A parameter update law is designed by the immersion and invariance method, and is used in conjunction with both the feedback linearization and backstepping control laws. Simulation results show that the responses obtained in the adaptive case are very similar to the known parameter case, and the parameter estimator converges to the true value.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.125.3-125
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• 2001

Recently, aircraft is designed to have high maneuverable at high angle of attack. However, it is very hard to obtain the accurate dynamic model for the high performance, because aerodynamic characteristics are nonlinear and include a lot of uncertainties. Therefore, nonlinear controller without considering uncertainties may degrade the control system performance. On this paper, to overcome these defects, the neural networks based adaptive nonlinear controller is proposed making use of the backstepping technique. Neural networks are implemented to guarantee robustness to uncertainties caused by aerodynamic coefficients variation. The main feature of the proposed controller is that the adaptive controller is developed under the assumption ...

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.32-43
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• 1999

Adaptive robust control scheme is introduced for flexible joint manipulator with nonlinearities and uncertainties. The system does not satisfy the matching condition due to insufficient actuators for each node. The control only relies on the assumption that the bound of uncertainty exists. Thus, the bounded value does not need to be known a prior. The control utilizes the update law by estimating the bound of the uncertainties. The control scheme uses the backstepping method and constructs a state transformation. Also, stability analysis is done for both transformed system and original system.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2667-2668
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• 2000

In this paper we consider the TORA system and use sliding observer and backstepping to design a robust controller for tracking problem.

• Journal of IKEEE
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• v.23 no.4
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• pp.1265-1272
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• 2019

We analyze the robustness of the existing predictor feedback controller for discrete-time linear systems with constant input delays against the structured model uncertainty. By modeling the constant input delay with a first-order PdE (Partial difference Equation), we replace the input delay with the PdE states. By applying a backstepping transformation, we build a target system that enables to construct an explicit Lyapunov function. Constructing the explicit Lyapunov function that covers the entire state variables, we prove the existence of an allowable maximum size of the structured model uncertainty to maintain stability and establish the robustness of the predictor feedback controller. The numerical example demonstrates that the stability of closed-loop system is maintained in the presence of the structured model uncertainty, and verifies the robustness of the predictor feedback controller.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.208-222
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• 2021

Managing with the presence of sea ice is the primary challenge in the operation of floating platforms in the Arctic region. It is widely accepted that offshore structures operating in Arctic conditions need station-keeping methods as well as ice management by icebreakers. Dynamic Positioning (DP) is one of the station-keeping methods that can provide mobility and flexibility in marine operations. The presence of sea ice generates complex external forces and moments acting on the vessel, which need to be counteracted by the DP system. In this paper, an icevaning control algorithm is proposed that enables Arctic offshore vessels to perform DP operations. The proposed icevaning control enables each vessel to be oriented toward the direction of the mean environmental force induced by ice drifting so as to improve the operational safety and reduce the overall thruster power consumption by having minimum external disturbances naturally. A mathematical model of an Arctic offshore vessel is summarized for the development of the new icevaning control algorithm. To determine the icevaning action of the Arctic offshore vessel without any measurements and estimation of ice conditions including ice drift, task and null space are defined in the vessel model, and the control law is formulated in the task space. A backstepping technique is utilized to handle the nonlinearity of the Arctic offshore vessel's dynamic model, and the Lyapunov stability theory is applied to guarantee the stability of the proposed icevaning control algorithm. Experiments are conducted in the ice tank of the Korea Research Institute of Ships and Ocean Engineering to demonstrate the feasibility of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1172-1177
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• 2003

In this paper, we propose an obstacle avoidance technique in trajectory tracking of nonholonomic wheeled mobile robots. Input-output linearized backstepping controller is used in trajectory tracking, and repulsive type control input for obstacle avoidance is added to it. The added input is generated by fuzzy logic. And we do not add the two inputs directly but combine them via fuzzy logic, which determines the ratings of each input. Some simulations are performed to show that with the proposed algorithm, the mobile robot can track its reference trajectory even if there are multiple obstacles on the trajectory of robot.