• 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.

• Smart Structures and Systems
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• v.19 no.5
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• pp.577-585
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• 2017

In this paper, an adaptive fuzzy sliding mode controller (AFSMC) is designed to reduce dynamic responses of seismically excited structures. In the conventional sliding mode control (SMC), direct implementation of switching-type control law leads to chattering phenomenon which may excite unmodeled high frequency dynamics and may cause vibration in control force. Attenuation of chattering and its harmful effects are done by using fuzzy controller to approximate discontinuous part of the sliding mode control law. In order to prevent time-consuming obtaining of membership functions and reduce complexity of the fuzzy rule bases, adaptive law based on Lyapunov function is designed. To demonstrate the performance of AFSMC method and to compare with that of SMC and fuzzy control, a linear three-story scaled building is investigated for numerical simulation based on the proposed method. The results indicate satisfactory performance of the proposed method superior to those of SMC and fuzzy control.

• 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.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.584-596
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• 2019

This paper presents a Modified Adaptive Complementary Sliding Mode Control (MACSMC) system for the longitudinal motion control of the Fully-Submerged Hydrofoil Craft (FSHC) in the presence of time varying disturbance and uncertain perturbations. The nonlinear disturbance observer is designed with less conservatism that only boundedness of the derivative of the disturbance is required. Then, a complementary sliding mode control system combined with adaptive law is designed to reduce the bound of stabilization error with fast convergence. In particularly, the modified complementary sliding mode surface which contains the estimation of the disturbance can reduce the switching gain and retain the normal performance of the system. Moreover, a hyperbolic tangent function contained in the control law is utilized to attenuate the chattering of the actuator. The global asymptotic stability of the closed-loop system is demonstrated utilizing the Lyapunov stability theory. Ultimately, the simulation results show the effectiveness of the proposed approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.12-18
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• 2011

This paper deals with a new adaptive fuzzy sliding mode controller and its application to an inverted pendulum. We propose a new method of adaptive fuzzy sliding mode control scheme that the fuzzy logic system is used to approximate the unknown system functions in designing the SMC of uncertain nonlinear systems. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. 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. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.8-14
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• 2000

In this paper, three adaptive sliding mode control algorithms, which self-tune both the sliding mode gain and the boundary layer thickness, are proposed. The first algorithm uses a gain adaptation rule is combined with the boundary layer thickness adaptatioin rule to satisfy the sliding condition. In the third algorithm, the computation burden of the second algorithm is reduced further, and therefore no extra cost is required for real-time implementation. Due to the mixed sliding mode gain and the boundary layer thickness adaptation scheme, the tracking error and the chattering of the control input can be reduced greatly.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode 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 generates the control input for 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 to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.109-117
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• 1999

In this paper, a direct adaptive control, based on Lyapunov Function Candidate, is applied to a nonlinear Gunner's Primary Stabilized Head Mirror system to derive a parameter adaptation scheme; furthemore, a nonlinear sliding mode control, but also compensating the error in identification of the parameters which are even varying of have uncertain values. The performance of the adaptive controller is determined by the tracking ability to a desired model under some disturbances and the slowly varying parameters of the system. Both adaptive scheme and sliding mode play an important fole in the improvement of the nonlinear system control.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.172-182
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• 2013

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.