• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2992-2994
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• 1999

This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the weight adjustment is developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Also, the tracking errors between the system outputs and the desired outputs converge to zero asymptotically. To evaluate the performance of the controller, the proposed method is applied to the trajectory control of the two-link manipulator.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2248-2250
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• 2003

This paper Backstepping design with Sliding Mode Control for AC Servo Systems. The robustness of sliding mode control can be used for backstepping technique to solve the uncertainty problem. A scalar design using Lyapunov function is developed for high-order systems. The result can be easily extended to non-linear system and used with many other sliding mode control results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.838-842
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• 2011

This paper proposes an online adaptive neuro-controller for a wind energy conversion system (WECS) that is a highly nonlinear system intrinsically. In real application, to obtain exact system parameters such as power coefficient, many measuring instruments and implementations are required, which is very difficult to perform. This shortcoming can be avoided by introducing neural network in the controller design in this paper. The proposed adaptive neural control scheme using radial-basis function network (RBFN) needs no system parameters to meet control objectives. Combining derivative estimator for wind velocity, the whole closed-loop system is shown to be stable in the sense of Lyapunov.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.331-333
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• 1995

A high performance motor drive system must have a good speed command tracking, a insensitivity to a parameter variation and sampling time. In this paper, a robust speed controller for an induction motor is proposed. The speed controller is fuzzy-sliding adaptive controller and its system continuously is varied. That is, only P gain act in dynamic state, I gain in steady-state. Because this system is a sort of adaptive control system, global stability analysis is used to Lyapunov function. Consequently, in this paper application of fuzzy sliding adaptive controller to induction motor controlled by vecter control is presented and the control system is digitally implemented within DSP.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.25-32
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• 1994

This paper presents a robust impedance controller design to coordinate a robot manipulator under system uncertainties while regulating external forces. By an impedance approach, the relationship between the motion and external forces is defined. Due to the system uncertainties, two kind of sliding mode control schemes based on the impedance approach are derived to ensure that the manipulator end-effector follows a desired trajectory and the force applied to end effector is regulated according to a target impendance. A stability condition is shown according to a sliding condition. To evaluate the devised control scheme, a numerical example is shown.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.211-224
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• 2019

This paper deals with a nonlinear controller based on saturation functions with variable parameters for set-point regulation and trajectory tracking control of an Autonomous Underwater Vehicle (AUV). In many cases, saturation functions with constant parameters are used to limit the input signals generated by a classical PD (Proportional-Derivative) controller to avoid damaging the actuators; however this abrupt bounded harms the performance of the controller. We, therefore, propose to replace the conventional saturation function, with constant parameters, by a saturation function with variable parameters to limit the signals of a PD controller, which is the base of the nonlinear PD with gravitational/buoyancy compensation and the nonlinear PD + controllers that we propose in this paper. Consequently, the mathematical model is obtained, considering the featuring operation of the underwater vehicle LIRMIA 2, to do the stability analysis of the closed-loop system with the proposed nonlinear controllers using the Lyapunov arguments. The experimental results show the performance of an AUV (LIRMIA 2) for the depth control problems in the case of set-point regulation and trajectory tracking control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2430-2434
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• 2003

This paper provides a new approach to analyze the stability of TCP Vegas, which is a kind of feedback-based congestion control algorithm. Whereas the conventional approaches use the approximately linearized model of the TCP Vegas along equilibrium points, this approach uses the exactly characterized dynamic model to get a new stability criterion via a piecewise and delay-dependent Lyapunov-Krasovskii function. Especially, the resulting stability criterion is formulated in terms of linear matrix inequalities (LMIs). Using the new criterion, this paper shows that the current TCP Vegas algorithm is stable in the sufficiently wide region of network delay and link capacity.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.191-196
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• 2003

This paper presents a method to design an adaptive controller for the kinematic model of a two-wheeled welding mobile robot (WMR) with unknown parameters. We propose a nonlinear controller based on the Lyapunov function to enhance the tracking properties of the WMR. The WMR can track any smooth curved welding path at a constant velocity of the welding point. The system has three degrees of freedom including two wheels and one torch slider. Torch slider motion is used for fast tracking. To design the tracking performance, the errors from WMR to steel wall is defined, and the controller is designed to drive the errors to zero as fast as possible. The effectiveness of the proposed controller is shown through simulation results.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2177-2178
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• 2011

In this paper, adaptive speed sensorless vector control, sliding mode observer to be present. Adaptive sliding mode observer of the motor stator coordinate system using the voltage equations of the rotor flux components are observed. Lyapunov function of the induction motor speed is estimated by the relationship further. In order to establish such a control scheme based on the way conventional PI controller and sliding mode observer annexing characteristics of the system through simulation and experiment were compared. Analyzed and compared according to the results presented confirmed the usefulness of the system.