• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.670-673
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• 1999

In this paper, we present a robust motion controller based on Adaptive-Fuzzy technique is proposed that multifunctional vehicle(MVR) for two DOF mobile robot can perform detailed inspection of physical conditions of sewage pipes as well as can effectively repair the damaged portions of the inner walls. The main difficulties in controlling this multifunctional robot vehicles lie in the fact that vehicles usually have three degrees of freedom in position and orientation in spite of having only two degrees of freedom for motion control in tracking mode. Decomposition of error between the reference posture and the current posture makes control of speed and steering possible. The Gyro compass part and Inclonometer of the robot is configured in order to realize position of robot. The proposed Adaptive-Fuzzy motion controller has two main characteristics: The one guarantees that the MVR follows the reference trajectory; the other one compensates the dynamics of the MVR. Simulation results are provided to validate the proposed controller. Experiments have been used to verify the effectiveness and robustness of the motion controller.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.101-105
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• 1989

The iterative learning controller makes the system output follow the desired output over a finite time interval through iterating trials. In this paper, first we discuss that the design problem of learning controller is originally the design problem of the inverse model. Then we show that the tracking error which is the difference between the desired output and the system output is reduced monotonically by properly modeled inverse system if the magnitude of the learning operator being introduced is bounded within the unit circle in complex domain. Also it would be shown that the conventional learning control method is a kind of extremely simplified inverse model learning control method of the objective controlled system. Hence this control method can be considered as a generalization of the conventional learning control method. The more a designer model the objective controlled system precisely, the better the performance of the approximated inverse model learning controller would be. Finally we compare the performance of the conventional learning control method with that of the approximated inverse model learning control method by computer simulation.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.293-294
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• 2007

This paper addresses the adaptive controller for efficiency optimization of induction motors. The paper describes an adaptive controller based on-line efficiency optimization control of a drive that uses a direct vector controlled induction motors. To improve the efficiency of the induction motors, it is important to find the optimal flux reference that minimize power loss. The proposed optimal flux reference is derived using a power loss function that is constructed with stator resistance losses, rotor resistance losses and core losses. The proposed sliding mode flux observer generates estimates the unmeasured rotor fluxes. An optimal efficiency controller has goal of maximizing the efficiency for a given speed and load torque. A simulation shows the effectiveness of the proposed technique.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.428-433
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• 1993

First, we propose a transparent and efficient design of discrete-time integral controllers accounting sampling skew. Based on the proposed controller, we derive a state-space representation of doubly coprime factorization including integral action. The representation is then used to obtain a convenient state-space parametrization of discrete-time two-degree-of-freedom integral controllers acconting sampling skew.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.622-627
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• 1994

In this paper, we discuss an application of LTR techniques to integral controller design for discrete-time non-minimum phase plant models. It is shown that the feedback property obtained by enforcing the conventional LTR procedure can be achieved by the partial LTR technique. In addition, we point out that the partial LTR technique provides more design freedom in shaping a target feedback property.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.37.5-37
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• 2001

A robust control for robot manipulators actuated by induction motors using neural networks(NNs) is considered. The control is designed to compensate for nonlinear dynamics associated with the mechanical subsystem and the electrical subsystems only with the measurements of link position, link velocity and stator winding currents. Two-layer NNs are used to approximate unknown functions occurring from parameter variation during backstepping design process. Specially, through the use of nonlinear observers for rotor flux, observed backstepping controller is designed to achieve uniform ultimately bounded link position tracking of the given reference signal ...

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.353-356
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• 1991

This paper proposes a robust direct adaptive control system implementation using a 80286 microprocessor-based system for controlling the speed of a DC servo motor. In this paper, assuming that the unmodeled dynamics of the plant are sufficiently small in the low-frequency range, the plant as linear time-invariant system is the second relative degree, we construct the direct adaptive control system with the algorithm considering plant unmodeled dynamics and execute the experiment, and compare the characteristics with those of PI algorithm's. It shows that an easy implementation of the built controller is due to the usage of software for the algorithm.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.666-669
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• 1991

This paper deals with the robustness of a direct adaptive pole-placement control algorithm for continuous time plants with unmodeled dynamics. In this paper, least squares method is used for controller parameter adaptation and covariance matrix update equation is modified by normalizing signal to guarantee the boundedness of all signals in the closed loop system. In the proposed algorithm, no a priori knowledge is required and it is shown that persistence of excitation condition is required to ensure the stability of the closed loop system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.130-135
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• 2001

In this paper, an observer-based adaptive controller is proposed to control the longitudinal motion of vehicles. The standard gradient method will be used to estimate the vehicle parameters, mass, time constant, etc. The nonlinear model between the driving force and the vehicle acceleration will be chosen to design the state observer for the vehicle velocity and acceleration. It will be shown that the proposed observer is exponentially stable, and that the adaptive controller proposed on this paper is stable. It will be proved that the errors of the relative distance, velocity and acceleration converge to zero asymptotically fast, and that the overall system is also asymptotically stable. The simulation results are presented to investigate the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1656_1657
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• 2009

This paper presents a new method for estimating rotor resistance of induction motor. The rotor resistance changes dramatically with temperature and frequency. Speed is controlled by PID as it is simplest and most intuitive control method. The change in rotor resistance has a great influence on the performance of IM. In this paper rotor resistance is estimated using Non Linear Disturbance Observer. The model uncertainty and system non linearity are treated as disturbance in this method. Using NDO it does not require an accurate dynamic model to achieve high precision motor control. Controller with NDO has more superior tracking performance. Simulation results are presented to show the validity of the proposed controller.