• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.330-335
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• 1994

In this paper, adaprive control and sliding mode control are combined to implement the proposed adaptive sliding mode control(ASMC) algorithm which is new approach to the control of industrial robot manipulator with external disturbances and parameter uncertainties. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The contribution of this method is that the parameters of the sliding surface are replaced by time varying parameters whose are calculated by an adaptation algorithm, which forces the errors to follow the behavior of a reference error model. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.522-527
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• 2013

In this study, dynamic response control of a flexible wing such as gust loads alleviation using sliding mode control method is presented. To achieve this purpose, trailing edge control surface of a flexible wing is used as control means generating the aerodynamic control force. Aeroservoelastic CASE) model consisting of aeroelastic plant, control surface actuator model, and gust model depicting the atmospheric turbulence is formulated in the state space. A sliding mode controller based on the estimated state vector is designed for active dynamic response control of flexible wing aeroservoelastic model. The performance of the controller designed is demonstrated via numerical simulation for the representative flexible wing model under atmospheric turbulence loading.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.799-804
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• 2003

Friction phenomenon can be described as two parts which are pre-sliding and sliding regions. In motion of the sliding region, friction forces depend on the velocity of the system and are known as Coulomb, stick-slip, stribeck effect and viscous friction. The pre-sliding region, which is before breakaway, depends on the position of the system. The motion of friction in the sliding region can be described as the LuGre model. But the pre-sliding motion of friction, which has hysteresis characteristics in general, is not known widely. Therefore, an improved friction model, which can describe the motion of friction in the pre-sliding region, is proposed in this paper. And simulation and experimental results show the effectiveness of the proposed friction model for precise tracking control systems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.131-136
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• 1997

This paper represent the variable structure adaptive mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in contiuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. the sampling process often forces the trajectory to oscillate in the neighborhood of the sliding surface. Adaptive control technique is particularly well-suited to robot manipulators where dynamic model is highly complex and may contain unknown parameters. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple sturcture is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control, Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.94-103
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• 2000

This paper describes the model identification and the discrete-time sliding mode control of electro-hydraulic servo systems which are composed of servo valves, double-rod cylinder and load mass. The controlled plant is identified as a 3th-order discrete-time ARMAX model obtained from the prediction error algorithm, where a nominal model and modeling errors are zuantitatively constructed. The discrete sliding mode controller for 3th-order ARMAX model is designed in discrete-time domain, where all states are observed from Kalman filter. The discrete sliding mode controller has better tracking performance than that obtained from continuous-time sliding mode controller, in experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.148-153
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• 1999

In this paper, it is proposed the adaptive-sliding mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Over the past decade, the design of advanced control systems for industrial robotic manipulators has been a very active area of research and two major design categories have emerged. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in continuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple structure is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results how that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

• Structural Engineering and Mechanics
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• v.26 no.4
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• pp.377-392
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• 2007

A discrete sliding mode control (SMC) method based on hybrid model of neural network and nominal model is proposed to reduce the vibration of flexible structures, which is a robust active controller developed by using a sliding manifold approach. Since the thick boundary layer will reduce the virtue of SMC, the multilayer feed-forward neural network is adopted to model the uncertainty part. The neural network is trained by Levenberg-Marquardt backpropagation. The design objective of the sliding mode surface is based on the quadratic optimal cost function. In course of running, the input signal of SMC come from the hybrid model of the nominal model and the neural network. The simulation shows that the proposed control scheme is very effective for large uncertainty systems.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.257-261
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• 2001

Nonlinear pulse width modulation (PWM) controlled system is considered to achieve control performance of thruster controlled spacecraft. The actual PWM controlled motions occur, very closely, around the average model trajectory. Furthermore nonlinear PWM controller design can be directly applied to thruster controlled spacecraft to determine thruster on-time. Sliding mode control for attitude tracking of three-axis thruster-controlled spacecraft is presented. Simulation results are shown which use modified Rodrigues parameters and sliding mode control law to achieve attitude tracking of a three-axis spacecraft with thrusters.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2669-2671
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• 2000

In this paper, a new model error following sliding mode control is considered with a novel sliding surface for the error. This novel sliding surface has nominal dynamics of an original state of the error system and makes it possible that the Sliding Mode Control(SMC) technique for the error of the model following is used with the various types of controllers. Its design is based on the augmented system whose dynamics have a higher order than that of the original error system. The reaching phase is removed by using an initial virtual state which makes the initial error state sliding function equal to zero.