• International Journal of Automotive Technology
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• v.1 no.1
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• pp.48-55
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• 2000

Two major roles of the traction control system (TCS) are to guarantee the acceleration performance and directional stability even in extreme road conditions, under which average drivers may not control the car properly. Commercial TCSs use experiential methods such as lookup table and gain-scheduling to achieve proper performance under various road and vehicle conditions. This paper proposes a new slip controller which uses the brake and the throttle actuator simultaneously. To avoid measurement problems and to get a simple structure, the brake controller and the throttle controller are designed using Lyapunov redesign method and multiple sliding mode control respectively. Through the hybrid use of brake and throttle controllers, the vehicle is insensitive to the variation of the vehicle mass, brake gain and road condition and can achieve the required acceleration performance. The proposed method is validated with simulations based on 15 DOF passenger car model.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.10
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• pp.110-118
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• 2000

An adaptive controller for trajectory tracking control of a pneumatic cylinder is proposed. The controller is directly derived by using Lyapunov function, and very simple and computationally efficient since it does not require the mathematical model or the parameter values of a pneumatic system. It is also shown that the system is bounded stable with the controller, and the size of tracking errors can be made arbitrarily small. The stability and the performance of the controller is also verified experimentally. The results of the experiments demonstrate that the proposed controller achieves more accurate trajectory tracking performance than a PD controller.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1070-1078
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• 2000

A nonlinear adaptive flight control system is proposed using a backstepping controller with neural network controller. The backstepping controller is used to stabilize all state variables simultaneously without the two-timescale assumption that separates the fast dynamics, involving the angular rates of the aircraft, from the slow dynamics which includes angle of attack, sideslip angle, and bank angle. It is assumed that the aerodynamic coefficients include uncertainty, and an adaptive controller based on neural networks is used to compensate for the effect of the aerodynamic modeling error. It is shown by the Lyapunov stability theorem that the tracking errors and the weights of neural networks exponentially converge to a compact set. Finally, nonlinear six-degree-of-freedom simulation results for an F-16 aircraft model are presented to demonstrate the effectiveness of the proposed control law.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.267-274
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• 1999

This paper proposes an adaptive sliding mode control scheme for an autopilot design of Skid-to-Turn (STT) missiles. The feedback linearization controller eliminates nonlinear terms in STT dynamics and makes the entire system linear. But the modeling errors in dynamics and the external disturbances exert bad influence on the performance of the feedback linearization controller. To handle these uncertainties, an adaptive control scheme is developed, where a bound of the uncertainties is estimated by an adaptive law based on a sliding surface. The asymptotic output tracking is proved by using the Lyapunov stability theory. Simulations for STT missiles illustrate the validity of the proposed scheme.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.777-780
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• 1991

The practical implementation of model reference adaptive systems(MRAS) using digital computer requires the derivation of discrete-time adaptation laws. This is specially important in the case of direct driver robot and light weight manipulator where inertia changes ang gravity effects are significant. We develope a discrete-time model reference adaptive control scheme for trajectory tracking of robot manipulator. Instead of the conventional Lyapunov approach hyperstabillty theory is more appealing than the Lyapunov approach. It is better suited to discrete time systems and offers more flexibility in design by providing additional free design parameters.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2292-2297
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• 2010

To improve the performances of Sawyer motors and to regulate yaw rotation, various feedback control methods have been developed. Almost all of these methods require information on the position, velocity or full state of the motor. Therefore, in this paper, a nonlinear observer is designed to estimate the full state of the four forcers in a Sawyer motor. The proposed method estimates the full state using only positional feedback. Generally, Sawyer motors are operated within a yaw magnitude of several degrees; outside of this range, Sawyer motors step out. Therefore, this observer design assumes that the yaw is within ${\pm}90^\b{o}$. The convergence of the estimation error is proven using the Lyapunov method. The proposed observer guarantees that the estimation error globally exponentially converges to zero for all arbitrary initial conditions. Furthermore, since the proposed observer does not require any transformation, it may result in a reduction in the commutation delay. The simulation results show the performance of the proposed observer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.603-610
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• 2000

In this paper, the direct and indirect adaptive controller are combined based on the Lyapunov synthesis approach. The Proposed controller is constructed from RBF Neural Network and weighting parameters are adjusted on-line according to some adaptation law. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. In the results, proposed controller has the main advantages of both the direct adaptive controller and the indirect adaptive controller. The effectiveness of the proposed control scheme is demonstrated through simulation results of control for one-link rigid robotics manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.5-8
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• 1996

This paper proposea a new adaptive algorithm to improve the performance fo a robust adaptive control system. This adaptive algorithm counteracts the effects of disturbances and makes the time derivative of Lyapunov function non-positive, $V{\leq}0$. As a result, the output error approaches zero as $t\;\rightarrow\;\infty$ not only in the presence of bounded disturbances, but also in the ideal case. The effectiveness of this proposed algorithm is demonstrated by the stability analysis and simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.478-488
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• 2003

A guidance scheme that is suitable for controlling the aircraft flight path is proposed. The concept of miss distance which is commonly used in the missile guidance laws, and Lyapunov stability theorem are effectively combined to obtain the aircraft's trajectory-tracking guidance law. Guidance commands are given in terms of speed and flight path angles, but they perfectly reflect any position and velocity errors between real aircraft trajectory and reference one. The proposed guidance law is easily integrated into the existing flight control system. The new guidance law was extensively tested with various mission scenarios and the fully nonlinear 6-DOF aircraft model. Furthermore, the new guidance law was compared with previous guidance schemes in nonlinear simulation. Results from the numerical simulation show that the proposed guidance law yields better performance than previous ones.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.247-250
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• 2003

In this paper, we propose a robust controller for motion control of n-link robot manipulators using visual feedback. The desired joint velocity and acceleration is obtained by the feature-based visual systems and is used in the joint velocity control loop for trajectory control of the robot manipulator. We design a robust controller that compensates for bounded parametric uncertainties of robot dynamics. The stability analysis of robust joint velocity control system is shown by Lyapunov Method. The effectiveness of the proposed method is shown by simulation results on the 5-link robot manipulators with two degree of freedom.