• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1005-1013
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• 2009

In this paper, the performance improvement of a decentralized brake system for railway rolling stocks is investigated. In order to verify the effectiveness of the decentralized brake system, it is compared to the truck unit brake system which has only one control unit per a truck. The adaptive sliding mode control scheme is used to realize a robust anti-slip brake control system. Through computer simulations, it is verified that the decentralized brake system has better braking performance than the truck unit brake system.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2525-2527
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• 2002

The objective of this paper is to design a force feedback controller for bilateral control of a master-slave manipulator system using adaptive fuzzy sliding mode control. In a bilateral control system, the motion of the master device is followed by slave the one. While the force applied to the slave is reflected on the master. In this paper a proposed controller applied to the system. Adding a switching control term to the input robustness is improved. Also the knowledge of the system dynamics is not needed. The computer simulation results show the performance of the proposed adaptive fuzzy sliding mode controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.47-52
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• 2012

This paper focuses on discrete-time sliding mode control with SIIM fuzzy adaptive switching gain. The adaptive switching gain is calculated using the simplified indirect inference fuzzy logic. Two fuzzy inputs are the normal distance from the present state trajectory to the switching function and the distance from the present state trajectory to the equilibrium state. The fuzzy output $f_{out}$(k) out f k is used to adjust the speed the adaptation law depending on the location of the state trajectory. The simulation results showed that the proposed method had no chattering in case of uncertain parameter without disturbance. Moreover the convergent rate of the switching gain was faster and more stable even in case of disturbance.

• Journal of Power Electronics
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• v.14 no.1
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• pp.105-114
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• 2014

The sliding mode control (SMC) strategy is applied to a permanent magnet synchronous machine vector control system in this study to improve system robustness amid parameter changes and disturbances. In view of the intrinsic chattering of SMC, a current sliding mode control method with a load sliding mode observer is proposed. In this method, a current sliding mode control law based on variable exponent reaching law is deduced to overcome the disadvantage of the regular exponent reaching law being incapable of approaching the origin. A load torque-sliding mode observer with an adaptive switching gain is introduced to observe load disturbance and increase the minimum switching gain with the increase in the range of load disturbance, which intensifies system chattering. The load disturbance observed value is then applied to the output side of the current sliding mode controller as feed-forward compensation. Simulation and experimental results show that the designed method enhances system robustness amid load disturbance and effectively alleviates system chattering.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1516-1520
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• 2005

We proposed the indirect adaptive fuzzy model based sliding mode controller to control a nonaffine nonlinear systems. Takagi-Sugano fuzzy system is used to represent the nonaffine nonlinear system and then inverted to design the controller at each sampling time. Also sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. The proposed controller and adaptive laws guarantee that the closed-loop system is stable in the sense of Lyapunov and the output tracks a desired trajectory asymptotically.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.527-532
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• 2005

In this paper, we proposed an adaptive fuzzy sliding control for unknown nonlinear systems using estimation of bounds for approximation errors. Unknown nonlinearity of a system is approximated by the fuzzy logic system with a set of IF-THEN rules whose consequence parameters are adjusted on-line according to adaptive algorithms for the purpose of controlling the output of the nonlinear system to track a desired output. Also, using assumption that the approximation errors satisfy certain bounding conditions, we proposed the estimation algorithms of approximation errors by Lyapunov synthesis methods. The overall control system guarantees that the tracking error asymptotically converges to zero and that all signals involved in controller are uniformly bounded. The good performance of the proposed adaptive fuzzy sliding mode controller is verified through computer simulations on an inverted pendulum system.

• Journal of Power Electronics
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• v.10 no.5
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• pp.505-517
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• 2010

In this paper, an intelligent sliding-mode speed controller for achieving favorable decoupling control and high precision speed tracking performance of permanent-magnet synchronous motor (PMSM) drives is proposed. The intelligent controller consists of a sliding-mode controller (SMC) in the speed feed-back loop in addition to an on-line trained wavelet-neural-network controller (WNNC) connected in parallel with the SMC to construct a robust wavelet-neural-network controller (RWNNC). The RWNNC combines the merits of a SMC with the robust characteristics and a WNNC, which combines artificial neural networks for their online learning ability and wavelet decomposition for its identification ability. Theoretical analyses of both SMC and WNNC speed controllers are developed. The WNN is utilized to predict the uncertain system dynamics to relax the requirement of uncertainty bound in the design of a SMC. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode speed controller. An experimental system is established to verify the effectiveness of the proposed control system. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulated and experimental results confirm that the proposed RWNNC grants robust performance and precise response regardless of load disturbances and PMSM parameter uncertainties.

• Journal of Electrical Engineering and information Science
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• v.3 no.1
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• pp.36-44
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• 1998

In this paper, a robust adaptive sliding mode control algorithm for accurate trajectory tracking of robot manipulators is proposed, with unknown parameters being estimated on-line. The controller is designed based on a Lyapunov method, which consists of adaptive feed-forward compensation part and a discontinuous control part. It is shown that, in the presence of the uncertainty and the disturbances arising from the actuator or some other causes, the tracking errors is bound to converge to zero asymptotically. An illustrative example is given to demonstrate the results of the propose method.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.226-228
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• 2006

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.161-163
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• 2005

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system. we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem. and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.