• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.547-555
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• 2003

This paper presents an adaptive control against uncertainties in tail-controlled STT (Skid-to-Turn) missiles. We derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1221-1224
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• 1992

To obtain a robustness which is one of important characteristics needed in servo drive, the sliding mode control method is used as a control strategy. However, the undesired phenomenon of chattering is a serious problem. In this paper, an adaptive chattering alleviation algorithm for variable structure system control is proposed to solve this serious problem. Digital controller using the theory of chattering alleviation control is applied to the position control problem of an induction motor system. Comparisons of this algorithm with other variable structure system control algorithms indicate that the chattering can be alleviated. This controller is implemented using IBM-PC(8088 CPU) which controls current controlled PWM inverter consisted of IGBT as a switching device to drive motor.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1860-1861
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• 2006

In this paper, we design a robust controller of biped robot system with uncertainties, using recurrent neural network. In our proposed control system, we use the self-recurrent wavelet neural network (SRWNN). The SRWNN makes up for the weak points in wavelet neural network(WNN). While the WNN has fast convergence ability, it dose not have a memory. So the WNN cannot confront unexpected change of the system. However, the SRWNN, having advantage of WNN such as fast convergence, can easily encounter the unexpected change of the system. For stable walking control of biped robot, we use sliding mode control (SMC). Here, uncertainties are predicted by SRWNN. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out computer simulations with a biped robot model to verify the effectiveness of the proposed control system,.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.63.6-63
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• 2002

The technique of backstepping have can avoid cancellations of useful nonlinearities. It is widely used in nonlinear adaptive control. But it is difficult to use this technique for uncertain nonlinear systems. Sliding mode control has robustness and application with feedback linearization. This paper shows that the robustness can be used for back stopping technique to solve the uncertainty problem and to improve the scalar design problem using Control Lyapunov function which is the motivation of back stepping technique with recursive design for high-order systems. In the respect of SMC, the result of this paper does not need to satisfy the matching condition.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.919-924
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• 2016

This paper proposes a robust control design method for improving the cornering stability of a personal electric vehicle equipped with in-wheel motors. In general, vehicles undergo severe parameter variations and unpredictable disturbances with respect to a wide range of driving conditions (e.g., road surface conditions and vehicle velocity conditions). For this reason, robust control design techniques are required to guarantee consistent driving performances and robustness against various driving conditions. In this paper, an adaptive sliding mode control method is employed to enhance cornering stability by controlling the direct-drive in-wheel motors independently. Additionally, in order to confirm the effectiveness of a proposed control method, real driving tests with an experimental personal electric vehicle are performed.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.134-144
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• 2017

This paper presents an adaptive control strategy for the speed control of a four-phase switched reluctance motor (SRM) in automotive applications. The main objective is to minimize the torque ripples, despite the unstructured uncertainties, time-varying parameters and external load disturbances. The bound of perturbations is not required to be known in the developing of the proposed adaptive-based control method. In order to achieve a smooth control effort, some properties are incorporated and the proposed control algorithm is constructed using the Lyapunov theorem where the closed-loop stability and robust tracking are ensured. The effectiveness of the proposed controller in rejecting high perturbed load torque with smooth control effort is verified with comparing of an adaptive sliding mode control (ASMC) and validated with experimental results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.3 s.246
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• pp.295-301
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• 2006

The wheel slip control systems are able to control the braking force more accurately and can be adapted to different vehicles more easily than conventional ABS systems. In order to achieve the superior braking performance through the wheel-slip control, real-time information such as the tire braking force at each wheel is required. In addition, the optimal target slip values need to be determined depending on the braking objectives such as minimum braking distance, stability enhancement, etc. In this paper, a robust wheel slip controller is developed based on the adaptive sliding mode control method and an optimal target slip assignment algorithm. An adaptive law is formulated to estimate the longitudinal braking force in real-time. The wheel slip controller is designed using the Lyapunov stability theory and considering the error bounds in estimating the braking force and the brake disk-pad friction coefficient. The target slip assignment algorithm is developed for the maximum braking force and searches the optimal target slip value based on the estimated braking force. The performance of the proposed wheel-slip control system is verified In simulations and demonstrates the effectiveness of the wheel slip control in various road conditions.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.10
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• pp.407-417
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• 1985

This paper describes a new method for the design of adaptive model-following control systems. This design concept is developed using the theory of slide mode. Authors present new results on the sliding control methodology to achieve accurate tracking for a class of multi-input multi-output, time-varying systems in the presence of parameter variations and disturbances. This algorithm can be easily applied to the multivariable control systems and obtained a smoother control signal in comparison to variable structure model following control systems. The design technique is easy and the control structure is simple. The design requires little computational effort. The control system is less sensitive to plant parameter variations and noise disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2088-2090
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• 1997

This paper consists of the speed sensorless vector control of induction motors with the estimation of rotor resistance. In the application of variable-speed induction motor drives, if an inaccurate rotor resistance is used because the rotor resistance can change due to skin effects and temperature variables, it is difficult to achieve a collect field orientation. In this paper, to overcome these difficulties adaptive algorithm is designed for rotor resistance identification. The proposed adaptive algorithm for rotor resistance estimation in the synchronous reference frame is applied by sliding mode current controller satisfing persistent excitation(PE) condition. Adaptive flux observer is here used for the purpose of estimating rotor flux and speed in the speed sensorless scheme. Computer simulations are carried out to verify the validity of the proposed algorithm.