• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.206-209
• /
• 1988

For feedback control of a linear dynamic system the optimum linear slace regulator (OLSR) can be implemented only if all state are available for feedback. This work demonstrates that when only the output state is available for feedback, a nonlinear controllers can be improved performance over that obtained by a proportional controller. This paper found the optimal control law by well-known dynamic programming and principles of optimality. Thus, performance of both proportional and nonlinear controllers is compared with performance of optimum linear state regulator.

• 제어로봇시스템학회:학술대회논문집
• /
• 1995.10a
• /
• pp.279-282
• /
• 1995

In this paper, a moving horizon control algorithm, which can be applied for a wide class of nonlinear systems with control and state constraints, is considered. In a neighborhood of the origin, a linear feedback controller is applied. Outside this neighborhood, a moving horizon control law is applied. The time taken to solve an optimal control problem is considered in the algorithm so that the proposed control law can be applied as an on-line controller.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2102-2104
• /
• 2001

This paper present the strategy of self-tuning nonlinear PID control using neural network. The nonlinear PID controller consists of a conventional PID controller and a neural network compensator. The neural network is trained by back-propagation algorithm. In this paper we propose modified back-propagation algorithm to improve learning speed. The results of simulation show the usefulness of the proposed scheme.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.38 no.11
• /
• pp.922-933
• /
• 1989

This paper deals with an indirect pole placement adaptive controller design problem for discrete-time plants with arbitrary zeros in the presence of unmodeled dynamics and/or disturbances. The plant and controller parameters are estimated by separate estimators. The nonlinear feedback is introduced so that the estimated plant has as high degree of controllability as possible. The nonlinear feedback will be used in a finite time, after which the control algorithm becomes a standard pole placement one.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.55 no.1
• /
• pp.14-16
• /
• 2006

We consider a web transport system. The objective of this paper is to design the controller such that desired tension and processing on web transport system. We propose the new design method hick is independent with operating condition. The proposed method used a nonlinear feedback to transform to linear system. We show a performance of controller via the simulation.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1128-1130
• /
• 1996

A canonical form observer design method for nonlinear systems is studied. Through this method, an observer of single link robot system with flexible joint is proposed. It is shown through simulation that the system can be stabilized when using the nonlinear feedback linearizing controller and the supposed observer.

• Proceedings of the KIEE Conference
• /
• 2008.04a
• /
• pp.217-218
• /
• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in order to increase an output of the PV array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.4
• /
• pp.329-339
• /
• 2003

A neural network based adaptive controller design method is proposed for reconfigurable flight control systems in the presence of variations in aerodynamic coefficients or control effectiveness decrease caused by control surface damage. The neural network based adaptive nonlinear controller is developed by making use of the backstepping technique for command following of the angle of attack, sideslip angle, and bank angle. On-line teaming neural networks are implemented to guarantee reconfigurability and robustness to the uncertainties caused by aerodynamic coefficients variations. The main feature of the proposed controller is that the adaptive controller is designed with assumption that not any of the nonlinear functions of the system is known accurately, whereas most of the previous works assume that only some of the nonlinear functions are unknown. Neural networks loam through the weight update rules that are derived from the Lyapunov control theory. The closed-loop stability of the error states is also investigated according to the Lyapunov theory. A nonlinear dynamic model of an F-16 aircraft is used to demonstrate the effectiveness of the proposed control law.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.4 no.1
• /
• pp.43-49
• /
• 1999

We propose a nonlinear feedback controller that can control the induction motors with high dynamic performance and high power efficiency by means of decoupling of motor speed and rotor flux. The nonlinear 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.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2008.10a
• /
• pp.315-318
• /
• 2008

In this paper proposed the solar tracking system to use a fuzzy control order to increase an output of the PV(Photovoltaic) array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.