• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.267-274
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• 1999

This paper proposes an adaptive sliding mode control scheme for an autopilot design of Skid-to-Turn (STT) missiles. The feedback linearization controller eliminates nonlinear terms in STT dynamics and makes the entire system linear. But the modeling errors in dynamics and the external disturbances exert bad influence on the performance of the feedback linearization controller. To handle these uncertainties, an adaptive control scheme is developed, where a bound of the uncertainties is estimated by an adaptive law based on a sliding surface. The asymptotic output tracking is proved by using the Lyapunov stability theory. Simulations for STT missiles illustrate the validity of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.315-319
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• 2016

This paper proposes a simple adaptive sliding mode control algorithm for controlling a permanent magnet synchronous generator (PMSG) of a MW-class direct-driven wind turbine system. The proposed adaptive sliding mode controller does not require accurate knowledge of the PMSG parameter or turbine torque values. The proposed controller can accurately track the reference angular speed computed by the maximum power point tracking(MPPT) algorithm. Finally, this paper gives Matlab/Simulink simulation results to verify the practicality and effectiveness of the proposed adaptive sliding mode controller.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1038-1043
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• 2010

In this paper, an adaptive sliding-mode formation control and collision avoidance are proposed for electrically driven nonholonomic mobile robots with model uncertainties and external disturbances. A sliding surface based on the leader-follower approach is developed to achieve the desired formation in the presence of model uncertainties and disturbances. Moreover, by using the collision avoidance function, the mobile robots can avoid the obstacles successfully. Finally, simulations illustrate the effectiveness of the proposed control system.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.173-179
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• 2003

In this paper, a real-time multibody vehicle dynamics and control model has been developed for a virtual reality intelligent vehicle simulator. The simulator consists of low PCs for a virtual reality visualization system, vehicle dynamics and control analysis system a control loading system, and a network monitoring system. Virtual environment is created by 3D Studio Max graphic tool and OpenGVS real-time rendering library. A real-time vehicle dynamics and control model consists of a control module based on the sliding mode control for adaptive cruise control and a real-time multibody vehicle dynamics module based on the subsystem synthesis method. To verify the real-time capability of the model, cut-in, cut-out simulations have been carried out.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.7
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• pp.75-84
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• 2003

To reduce the effects of the uncertainties due to the modeling error and aerodynamic coefficients, a nonlinear adaptive control system based on neural networks is proposed . Neural networks parameters are adjusted by using an adaptive law. The sliding mode control scheme is used to compensate for the effect of the approximation error of neural networks. Control parameters and neural networks structures are optimized to obtain better performance by using the genetic algorithm. By introducing the concept of multi-groups of populations, the genetic algorithm is modified so that individuals and groups can be simultaneously evolved . To verify the performance of the pro posed algorithm, the optimized neural networks control system is applied to an aircraft longitudinal dynamics.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.228-234
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• 2005

In this paper, we proposed a self tuning adaptive fuzzy sliding control algorithms using gadient descent method to reduce chattering phenomenon which is viewed in variable control system. In design of FLC, fuzzy control rules are obtained from expert's experience and intuition and it is very difficult to obtain them. We proposed an adaptive algorithm which is automatically updated by consequence part parameter of control rules in order to reduce chattering phenomenon and simultaneously to satisfy the sliding mode condition. The proposed algorithm has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2135-2137
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• 2002

In this paper to overcome drawback of FLC an adaptive fuzzy sliding mode controller is proposed. The fuzzy basis function to describe the fuzzy system is introduced. The system parameter in sliding mode are estimated by the indirect adaptive fuzzy control. Adaptive laws for fuzzy parameters and fuzzy rule structure are established so that the whole system is suable in the sense of Lyapunov stability. The computer simulation results for inverted pendulum system show the performance of the proposed fuzzy sliding mode controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.418-423
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• 2003

In order to describe the upper bound of the uncertainties without any information of the structure, we assume that the upper bound is represented as a Fredholm integral equation of the first kind, that is, an integral of the product of a predefined kernel with an unknown influence function. Based on the improved Lyapunov function, we propose an adaptation law that is capable of estimating the upper bound and we design a sliding mode control, which controls effectively for uncertain dynamic systems.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.331-333
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• 1995

A high performance motor drive system must have a good speed command tracking, a insensitivity to a parameter variation and sampling time. In this paper, a robust speed controller for an induction motor is proposed. The speed controller is fuzzy-sliding adaptive controller and its system continuously is varied. That is, only P gain act in dynamic state, I gain in steady-state. Because this system is a sort of adaptive control system, global stability analysis is used to Lyapunov function. Consequently, in this paper application of fuzzy sliding adaptive controller to induction motor controlled by vecter control is presented and the control system is digitally implemented within DSP.

• Journal of Power System Engineering
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• v.17 no.4
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• pp.120-130
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• 2013

An adaptive PID sliding mode controller is proposed for the position control of electro-hydrostatic actuator(EHA) systems with system uncertainties and saturation in the motor. An EHA prototype is developed and system modeling and parameter identification are executed. Then, adaptive PID sliding mode controller and optimal anti-windup PID controller are designed and the performance and robustness of the two control systems are compared by experiment. It was found that the adaptive PID sliding mode control system has better performance and is more robust to system uncertainties than the optimal anti-windup PID control system.