• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.7
• /
• pp.332-338
• /
• 2000

In this paper, a robust nonlinear excitation controller is proposed to achieve both voltage regulation and system stability enhancement for single machine-infinite power systems. The proposed method employs backstepping technique and combines this with an adaptation algorithm for estimating the effective reactance of transmission line, thereby leading to adaptive nonlinear control. Simulation results show that power that angle stabilization as well as voltage regulation is achieved in a satisfactory manner, regardless of the system operating conditions and system structure.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.spc2
• /
• pp.308-314
• /
• 2005

Transient stabilization with voltage regulation is investigated for a synchronous generator when the mechanical power is perturbed to any unknown value within its physical bounds so that the operating point of the system shifts to an unknown point. An adaptive excitation controller is designed based on the backstepping method with tuning functions. It will be shown that the adaptive control law proposed can achieve the convergence of the system states to the new equilibrium point in correspondence with the real value of the unknown mechanical power and the regulation of the terminal voltage to the required value. Simulation results are given to demonstrate the effectiveness of the proposed controller for the transient stabilization and voltage regulation.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.47 no.2
• /
• pp.16-24
• /
• 2010

This paper is proposed a novel fuzzy disturbance observer based on backstepping method for nonlinear systems with unknown disturbance. Using fuzzy logic systems, a fuzzy disturbance observer with the disturbance observation input is introduced for unknown disturbance. To guarantee that the proposed disturbance observer estimates the unknown disturbance, the disturbance observation error dynamic system is employed. Under the framework of the backstepping design, the fuzzy disturbance observer is constructed recursively and an adaptive laws and the disturbance observation input are derived. Numerical examples are given to demonstrate the validity of our proposed disturbance observer for nonlinear systems.

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

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.1505-1506
• /
• 2008

In this paper, a robust adaptive backstepping control is developed for efficiency optimization of induction motors with uncertainties. The proposed control scheme consists of efficiency flux control(EFC) using a sliding mode adaptive flux observer and robust speed control(RSC) using a function approximation for mechanical uncertainties. In EFC, it is important to find the flux reference to minimize power losses of induction motors. Therefore, we proposed the optimal flux reference using the electrical power loss function. The sliding mode flux observer is designed to estimate rotor fluxes and variation of inverse rotor time constant. In RSC, the unknown function approximation technique employs nonlinear disturbance observer(NDO) using fuzzy neural networks(FNNs). The proposed controller guarantees both speed tracking and flux tracking. Simulation results are presented to illustrate the effectiveness of the approaches proposed.

• Proceedings of the KIPE Conference
• /
• 2006.06a
• /
• pp.526-528
• /
• 2006

An adaptive output-feedback neural control problem of SISO strict-feedback nonlinear system is considered in this paper. The main contribution of the proposed method is that it is shown that the output-feedback control of the strict-feedback system can be viewed as that of the system in the normal form. As a result, proposed output-feedback control algorithm is much simpler than the previous backstepping-based controllers. Depending heavily on the universal approximation property of the neural network (NN) only one NN is employed to approximate lumped uncertain nonlinearity in the controlled system.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.1
• /
• pp.51-60
• /
• 2007

This paper describes a visual tracking control law of an Unmanned Aerial Vehicle(UAV) for monitoring of structures and maintenance of bridges. It presents a control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position to define a desired trajectory in an unknown 3D environment. The proposed method uses the homography matrix computed from the visual information and derives, using backstepping techniques, an adaptive nonlinear tracking control law allowing the effective tracking and depth estimation. The depth represents the desired distance separating the camera from the target.

• Ocean Systems Engineering
• /
• v.12 no.2
• /
• pp.159-172
• /
• 2022

To ensure stable performance, adaptive regulators with new theories are designed for steel-covered offshore platforms to withstand anomalous wave loads. This model shows how to control the vibration of the ocean panel as a solution using new results from Lyapunov's stability criteria, an evolutionary bat algorithm that simplifies computational complexity and utilities. Used to reduce the storage space required for the method. The results show that the proposed operator can effectively compensate for random delays. The results show that the proposed controller can effectively compensate for delays and random anomalies. The improved prediction method means that the vibration of the offshore structure can be significantly reduced. While maintaining the required controllability within the ideal narrow range.

• Proceedings of the KIEE Conference
• /
• 2007.04b
• /
• pp.134-137
• /
• 2007

LMTT(Linear Motor-based Transfer Technology) 시스템은 항만 컨테이너 이송장치의 자동화 시템으로 기술적 포화상태에 이른 AGV (Automated Guided Vehicle)의 대체 수단으로 제안되었다. 본 논문에서는 PMLSM (Permanent Magnetic Linear Synchronous Motor)을 기본 구조로 한 LMTT에서 발생할 수 있는 레일과 차체간의 인척력 변화와 다양한 부하 중량에 대한 시스템 내부 변수의 변동에 적응할 수 있는 제어기 설계에 초점을 두었다. 그렇게 됨으로써 제어시 큰 방해요소로 작용하는 마찰력에 의한 백래쉬 및 데드존을 최소화하여 속응성 및 정밀도를 향상시키고자 하였다.

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