• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1507-1508
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• 2008

In this paper, we propose a direct robust adaptive backstepping speed controller for induction motors system. A robust adaptive backstepping controller is designed using high order neural networks(HONN), which avoids the singularity problem in adaptive nonlinear control. The stability of the resulting adaptive system with proposed adaptive controller is guaranteed by suitable choosing the design parameter and initial conditions. HONN are used to approximate most of uncertainties which are derived from unknown motor parameters, load torque disturbances and unknown nonlinearities. The applicability of the proposed scheme is tested simulation.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2138-2139
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• 2002

In this paper we presents a speed controller for separately excited DC motor using adaptive backstepping technique. The motor was modeled in two local areas the first model is a linear one when speed is under base speed, the other is nonlinear one when field weakening is used to obtain the speed well above base speed. Then linear robust state feedback controller was designed for the linear model while adaptive backstepping controller was designed for the nonlinear model. The adaptive backstepping technique takes system nonlinearity into account in the control system design stage. The proposed controller is proved to be asymptotically stable by the Lyapunov stability theory and some simulations have been carried out to test.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.682-684
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• 1997

In the design of nonlinear control systems separation principle does not hold. Moreover even an exponentially decaying disturbances can destabilize a nonlinear system and lead to finite escape time from certain initial conditions. So we present a simple output feedback speed controller of induction motors which is designed to minimize the effects of observation error using the Kanellakopoulos et al's interlaced controller-observer design method. Simulation shows that the proposed controller has desired performance like another complex controllers.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2753-2755
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• 2000

In this paper, the robust position tracking cotroller for a brushless DC motor driving a one-link robot manipulator is proposed. By using the backstepping approach, the adaptive and robust controller is appropriately designed to ensure global stability. The proposed robust backstepping controller can compensate for estimation errors in system parameters in the system with no structural changes in the controller and without destruction of the stability. The closed-loop stability of the system is shown using Lyapunov techniques. The tracking errors are shown to be globally uniformly bounded.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.231-234
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• 1993

This paper deals with the design of an adaptive controller using neural network. We present RBFMLP Neural Network which consists of serial-connected two networks - Radial Basis Function Network and Multi Layer Perceptron, and then design a controller based on proposed networks with the adaptive control system structure, The plant and parameters of the controller are identified by the neural networks. We use the dynamic backpropagation algorithm for the learning of networks. Simulations represent the superiorities of the proposed network and the controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.60-67
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• 2002

This paper presents a control approach for designing a self tuning fuzzy controller for a synchronous generator excitation and SVC system. A combination of thyristor-controlled reactors and fixed capacitors (TCR-FC) type SVC is recognized as having the most flexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage. The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly. Using input-output data pair obtained from PSS, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed steepest decent method. The related simulation results show that the proposed fuzzy controller is more powerful than the conventional ones.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.391-393
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• 1992

This paper proposes an adaptive control system using a 80286 microprocessor-based system and DC servo motors for the control of flexible joint manipulator. In this paper, we construct the controller based on a singular perturbation strategy damping out the elastic oscillations at the joints. we added to the controller the compensator for damping the joint and the term for decreasing the position error between the actuator and the link in order to improve the asymptotical convergence of the position of the link. It is shown that the implementation of this control algorithm can be practical.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.128-137
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• 2007

A robust adaptive controller design for a class of Markovian jump parametric -strict-feedback systems is given. The disturbances considered herein include both uncertain nonlinearities and Wiener noises of unknown covariance. And they satisfy some bound-conditions. By using stochastic Lyapunov method in Markovian jump systems, a switching robust adaptive controller was obtained that guarantees global uniform ultimate boundedness of the closed-loop jump system.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.588-591
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• 1998

In this paper, we present a robust adaptive backstepping output feedback controller for nonlinear systems perturbed by unmodelled dynamics and disturbances. Especially, backstepping technique with modular approach is used to separately design controller and identifier. The design of identifier is based on the observer-based scheme which possesses a strict passivity property of observer error system. We will use Switching-${\sigma}$ modification at the update law and the modified control law to attenuate the effects of undodelled dynamics and disturbances for nonlinear systems.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.285-286
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• 2007

This paper presents a robust controller in order to handle the guide rail vibrations of Bridge Inspection System. While a Bridge Inspection Robot moves on guide rails with vibration by weight occurs. Therefore, Guide rail as structure like cantilever beam appears vibration by weight of Bridge Inspection Robot. The Z axis of Bridge Inspection Robot operates with Scissors structure. Bridge Inspection Robot is used 'PID Controller based on Sliding Mode control' for position control with Z axis. At the result of, this paper is applied to simulation about position control regarding vibration to occur with Z axis.