• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.1031-1035
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• 2001

In this paper, a robust recursive control approach for nonlinear system, which is based on Lyapunov stability, is proposed. The proposed method can apply to extended systems including cascaded systems and the stability is guaranteed in the sense of Lyapunov. The recursive design procedure so called “robust recursive control approach” is used to find a stabilizing robust controller and simultaneously estimate the uncertainty parameters. First, a nonlinear model with uncertainties whose bounds are unknown is derived. Then, unknown bounds of uncertainties are estimated. By using these estimates, the stabilizing robust controller is updated at each step. This approach is applied to the pitch autopilot design of a nonlinear missile system and simulation results indicate good performance.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.262-269
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• 2005

In this paper, a nonlinear robust control approach is applied to design a controller for the Static Synchronous Compensator (STATCOM). A robust control dynamic model of STATCOM in a one-machine, infinite-bus system is established with consideration of the torque disturbance acting on the rotating shaft of the generator set and the disturbance to the output voltage of STATCOM. A novel recursive approach is utilized to construct the energy storage function of the system such that the solution to the disturbance attenuation control problem is acquired, which avoids the difficulty involved in solving the Hamilton-Jacobi-Issacs (HJI) inequality. Sequentially, the nonlinear disturbance attenuation control strategy of STATCOM is obtained. Simulation results demonstrate that STATCOM with the proposed controller can more effectively improve the voltage stability, damp the oscillation, and enhance the transient stability of power systems compared to the conventional PI+PSS controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1771-1776
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• 2003

In mobile robot navigation, one of the key problems is the pose estimation of the mobile robot. Although the odometry can be used to describe the motions of the mobile robots quite simple and accurately, the validities of the models are limited by a number of error sources contaminating the encoder outputs so that applying the conventional extended Kalman filter to these nominal model does not yield the satisfactory performance. As a remedy for this problem, we consider the uncertain nonlinear kinematic model of the mobile robot that contains the norm bounded uncertainties and also propose a new robust extended Kalman filter based on the Krein space approach. The proposed robust filter has the same recursive structure as the conventional extended Kalman filter and can hence be readily designed to effectively account for the uncertainties. The computer simulations will be given to verify the robustness against the parameter variation as well as the reliable performance of the proposed robust filter.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.150-155
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using digital signal processors for robot manipulators. TMS3200C50 is used in implementing real-time adaptive control algorithms provide advanced performance for robot manipulator. In this paper an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm and controller parameters are detemined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.445-445
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• 2000

This paper proposes the MIMO indirect adaptive fuzzy controller to control the two-link manipulators. The input-output linearization technique, equivalent control input plus integral term, augmented error model and recursive least square adaptive law are used fer the controller. The linear type of fuzzifier-defuzzifier fuzzy logic system used for nonlinear function makes easy to farm the error model and able to follow the adaptive system approach. Such that control approach, the control system is not required joint speed and accerelation measurement and easy to implement and tune. The simulation results showed that the proposed controller has good control performance, stability, very small tracking error, decoupling, fast convergence, robust to parameter variation and load.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.754-758
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS320C50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator, In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters we determined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.50-56
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• 1999

This paper presents consideration on validity of instantaneous correlation power theory. The proposed power theory is defined and analyzed by time domain approach, thus it is easy to understand and instrument. The power is decomposed into active, fundamental reactive and harmonics components based on the autocorrelation and crosscorrelation signal techniques between voltage and current waveforms. On the compensation property, active power filter deal with three components only. Also, for real time control of active power filter, the power models with difficult concept are not cost effective. To verify the validity of the instantaneous correlation power theory, experimental work for voltage type DSP based active power filter is achieved. The power of thyristor controlled motor drives is decomposed into three orthogonal components by proposed power theory. From compensation results, validity of proposed theory is confirmed. feedback controller needs the information on some motor parameters. New recursive adaptation algorithms for rotor resistance and mutual inductance which can be applied to our nonlinear feedback controller are also presented in this paper. The recursive adaptation algorithms make the estimated values of rotor resistance and mutual inductance track their real values. Some simulation and experimental results show that the adaptation algorithms are robust against the variation of stator resistance and stator inductance.