• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.473-480
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• 2000

A fuzzy PID controller is proposed for the posture control of a two DOF robot vehicle inspecting the defects of the inner wall of sewage pipes. The main difficulty in controlling these kinds of vehicles lies in that the center of two mobile shafts does not coincide with the weight center of the vehicle due to its long and wide shape. In this case the previous controller, based on the assumption that the gap between these centers are small, can not guarantee satisfactory transient response characteristics. In this paper, this gap is included in the mathematical modelling of the robot kinematics, and in order to compensate the unsatisfactory transient response characteristics, the fuzzy PID controller is proposed. This controller tunes the PID control gains with respect to the current state of the errors between the reference and the current postures. A series of simulations has been performed to investigate the tracking performance of the proposed controller for the lane changing path and the robustness to the external disturbance. The simulation results show that the proposed controller has a satisfactory tracking performance in the transient state as compared with that of the backstepping control given in reference.

• 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.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.1-6
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• 2009

In this paper, we design a dynamic state feedback smooth stabilizer for a nonlinear system whose Jacobian linearization may have uncontrollable mode because its eigenvalues are on the right half-plane. After designing an augmented system, a dynamic exponent scaling and backstepping enable one to explicitly design a smooth stabilizer and a continuously differentiable Lyapunov function which is positive definite and proper. The convergence of the designed controller is proved by the new notion 'degree indicator'.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2365-2377
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• 2017

This paper addresses two interrelated problems concerning the tracking control of pod propulsion unmanned surface vessel (USV), namely, the modeling of pod propulsion USV, and tracking controller design. First, based on MMG modeling theory, the model of pod propulsion USV is derived. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network approximation and adaptive method. Meanwhile, unlike some existing tracking methods for surface vessel whose control algorithms suffer from "explosion of complexity", a novel neural shunting model is introduced to solve the problem. Using a Lyapunov functional, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of pod propulsion USV is proved; second, the neural shunting model is used to solve the problem of "explosion of complexity", and this is a combination of knowledge in the field of biology and engineering; third, the developed controller is able to capture the uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. Numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.253-258
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• 2001

This paper introduces a simple nonlinear adaptive control method for pipeline inspection gauge (PIG) flow in natural gas pipeline. The dynamic behavior of the PIG depends on the different pressure across its body and the bypass flow through it. The system dynamics includes: dynamics of driving gas flow behind the PIG, dynamics of expelled gas in front of the PIG, and dynamics of the PIG. The method of characteristics (MOC) and Runger-Kuta method are used to solve the dynamics of flow. The PIG velocity is controlled through the amount of bypass flow across its body. A simple nonlinear adaptive controller based on the backstepping method is introduced. To derive the controller, three system parameters should be measured: the PIG position, its velocity and the velocity of bypass flow across the PIG body. The simulation has been done with a pipeline segment in the KOGAS low pressure system, Ueijungboo-Sangye line to verify the effectiveness of the proposed controller. Three cases of interest are considered: the PIG starts to move at its launcher, the PIG arrives at its receiver and the PIG restarts after stopping in the pipeline by obstruction. The simulation results show that the proposed nonlinear adaptive controller attained good performance and can be used for controlling the PIG velocity.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.10
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• pp.1031-1039
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• 2013

This paper presents gain optimization of a 6-DOF underwater robotic platform with 4 rotatable thrusters. To stabilize the 6-DOF motion of the underwater robotic platform, a back-stepping controller is designed with 6 proportional gains and 6 derivative gains. The 12 gains of the backstepping controller are optimized to decrease settling time in step response in 6-DOF motion independently. Stability criterion and overshoots are used as a constraint of the optimization problem. Trust-region algorithm and hybrid Taguchi-Random order Coordinate search algorithm are used to determine the optimal parameters, and the results by two methods are analyzed. Additionally, the resulting controller shows improved performance under disturbances.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1761-1766
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• 2011

This paper presents obstacle avoidance of Leader-Follower formation. The follower robot maintain the formation with leader robot and avoid the detected obstacle. When obstacle is detected, follower robot avoid it considering leader robot and follower robot position and follower robot and obstacle position. In addition, follower robot avoid obstacle irrespective of obstacle size. Controller of follower robot is designed to satisfy Lyapunov stability by backstepping method. Simulation results shows that the designed controller has a stable performance.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1848-1849
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• 2006

The new robust controller design method is proposed for the flight control systems with model uncertainties. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the "explosion of complexity" problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.