• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1033-1039
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• 2007

In this paper, we design a terminal sliding mode controller based on self-recurrent wavelet neural network (SRWNN) for the second-order nonlinear systems with model uncertainties. The terminal sliding mode control (TSMC) method can drive the tracking errors to zero within finite time in comparison with the classical sliding mode control (CSMC) method. In addition, the TSMC method has advantages such as the improved performance, robustness, reliability and precision. We employ the SRWNN to approximate model uncertainties. The weights of SRWNN are trained by adaptation laws induced from Lyapunov stability theorem. Finally, we carry out simulations for Duffing system and the wing rock phenomena to illustrate the effectiveness of the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.719-727
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• 2002

We proposed a decoupled adaptive fuzzy sliding-mode control scheme for a class of fourth-order nonlinear systems. The system is decoupled into two second-order systems such that each subsystem has a separate control target expressed in terms of sliding surface. For these sliding surfaces, we define main and sub target conditions. and, we made intermediate variables which are interconnected both surface conditions from the sub target sliding surface. Then, Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target sliding surface including intermediate variables. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of sliding-mode control, are changed according to the adaptive law. With such a design scheme, we not only maintain the distribution of membership functions over state space but also reduce the computing time considerably. We apply the decoupled adaptive sliding-mode control to a nonlinear Cart-Pole system and confirms the validity of the proposed approach.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.145-150
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• 2005

We proposed the indirect adaptive fuzzy model based sliding mode controller to control 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 Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.25-32
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• 1995

Nonlinear depth control algorithms for the hovering system of underwater vehicles are presented. In this paper, a nonlinear effect in heave motion for underwater vehicles, a deadzone effect of the flow control valve in the hovering tank and an impact disturbance are considered. In this situation, in order to choose a desirable controller, sliding mode controller and fuzzy sliding mode controller are designed and compared. The computer simulation results show that the fuzzy sliding mode control system is more suitable in order to maintain a desirable depth of an underwater vehicle with a deadzone and impact disturbance.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1759-1760
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• 2008

This paper proposes a neural network(NN)-based adaptive sliding mode controller for discrete-time nonlinear systems. By using disturbance estimation technique, a sliding mode controller is designed, which forces the sliding variable to be zero. Then, NN compensator with hidden-layer-to-output-layer weight update rule is combined with sliding mode controller in order to reduce the error of the estimates of both disturbances and nonlinear functions. The whole closed loop system rejects disturbances excellently and is proved to be ultimately uniformly bounded(UUB) provided that certain conditions for design parameters are satisfied.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1810-1815
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• 2003

Sliding mode control with nonlinear interpolation in the boundary layer is proposed. A modified sigmoid function is used for nonlinear interpolation in the boundary layer and its parameter is tuned by a fuzzy logic controller. The fuzzy logic controller that takes the distance between the system state and the sliding surface as its input guides the choice of parameter of the modified sigmoid function and the parameter is on-line tuned. Owing to the decreased thickness, the proposed method has better tracking performance than the conventional linear interpolation method. To demonstrate its performance, the proposed control algorithm is applied to a simple nonlinear system model.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.221-224
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• 2000

We consider one of robust controller, fuzzy-sliding mode controller dealing with model uncertainty, simplified representation of nonlinear system, changed parameters of plant. We propose fuzzy-sliding mode algorithm which provides control input that has system states approaching the choosed sliding surface. This fuzzy controller has a rule base to get initial states converged on sliding surface. This algorithm Is applied to a transfer function of DC motor to be modeled simply and do position control of DC motor due to system parameters. We compare fuzzy-sliding mode controller to both sliding mode controller and fuzzy controller to identify roust control.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.175-180
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• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1716-1717
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• 2007

In this paper, a second order fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for a nonlinear system with unknown dynamics. The chattering effect that is a representative disadvantage of the sliding mode control is avoided by using the second order sliding mode control instead of the first order sliding mode control. The proposed sub-controller is composed of the equivalent control that is approximated by an online rule regulation sheme and the hitting control that is used to constrain the states of the sub-system to maintain on the sub-sliding surface and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller