• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.125-130
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• 2009

A robust friction compensation scheme is proposed in this paper. The recurrent fuzzy neural network and friction parameter observer are developed with sliding mode based controller in order to obtain precise position tracking performance. For a servo system with incomplete identified friction parameters, a proposed control scheme provides a satisfactory result via some experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.320-328
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• 2003

This paper proposes a new nonlinear adaptive guidance law. Fourth order state equation for integrated guidance and control loop is formulated considering target uncertainties and control loop dynamics. The state equation is further changed into the normal form by nonlinear coordinate transformation. An adaptive nonlinear guidance law is proposed to compensate for the uncertainties In both target acceleration and control loop dynamics. The proposed law adopts the sliding mode control approach with adaptation fer unknown bound of uncertainties. The present approach can effectively solve the existing guidance problem of target maneuver and the limited performance of control loop. We provide the stability analyses and demonstrate the effectiveness of our scheme through simulations.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.1
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• pp.71-80
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• 2009

The response characteristics of EHA systems are sensitive to the temperature change of working fluid because the temperature of working fluid causes the variation of system parameters such as effective bulk modulus and viscous friction coefficient. In this paper, a precise position control of EHA system using the adaptive sliding mode control system is suggested. The adapted system parameters such as effective bulk modulus and viscous friction coefficient can be used for monitoring failures in the EHA system which has potential applications in the industrial fields. Not only the accuracy of adapted system parameters but also the improved performance and robustness in a given reference position of the cylinder are verified by computer simulation using AMESim software.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.146-152
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• 2014

In this paper, a new adaptive nonsingular terminal sliding mode control theory based impact angle guidance law for intercepting maneuvering targets was documented. In the design procedure, a new adaptive law for target acceleration bound estimation was presented, which allowed the proposed guidance law to be used without the requirement of the information on the target maneuvering profiles. With the aid of Lyapunov stability criteria, the finite-time convergent characteristics of the line-of-sight angle and its derivative were proven in theory. Numerical simulations were also performed under various conditions to demonstrate the effectiveness of the proposed guidance law.

• Journal of Power Electronics
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• v.9 no.4
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• pp.582-592
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• 2009

This paper proposes a new speed sensorless direct torque and flux controlled interior permanent magnet synchronous motor (IPMSM) drive. Closed-loop control of both the torque and stator flux linkage are achieved by using two proportional-integral (PI) controllers. The reference voltage vectors are generated by a SVM unit. The drive uses an adaptive sliding mode observer for joint stator flux and rotor speed estimation. Global asymptotic stability of the observer is achieved via Lyapunov analysis. At low speeds, the observer is combined with the high frequency signal injection technique for stable operation down to standstill. Hence, the sensorless drive is capable of exhibiting high dynamic and steady-state performances over a wide speed range. The operating range of the direct torque and flux controlled (DTFC) drive is extended into the high speed region by incorporating field weakening. Experimental results confirm the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1276-1278
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• 2005

In this paper, we propose an adaptive sliding mode observer-based control of induction motors with uncertainties. The proposed adaptive sliding mode flux observer generates estimates both for the unknown parameters(load torque and rotor resistance) and for the unmeasured state variable (rotor fluxes); they converge to the corresponding true value under persistency of excitation which actually holds in typical operating conditions. The proposed controller guarantees speed tracking and bounded signals for every initial condition of the motor. Simulations show that all estimation errors tend quickly to zero so that high tracking performances are achieved both for speed and rotor flux.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.747-752
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• 2006

In this paper, the adaptive fuzzy sliding mode controller with two systems is designed. The existing sliding mode controller used to $approximation{\^{u}}(t)$ with discrete sgn function and sat function for keeping the state trajectories on the sliding surface[1]. The proposed controller decrease the disturbance for uncertain control gain and This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems ate 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 ate demonstrated. Futhermore, fuzzy tuning improve tracking abilities by changing some sliding conditions. In the traditional sliding mode control, ${\eta}$ is a positive constant. The increase of ${\eta}$ has led to a significant decrease in the rise time. However, this has resulted in higher overshoot. Therefore the proposed ${\eta}$ tuning AFSMC improve the performances, so that the controller can track the trajectories faster and more exactly than ordinary controller. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Smart Structures and Systems
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• v.11 no.3
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1081-1087
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• 2006

Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.