• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.89-90
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• 2006

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.315-320
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• 2003

This paper presents a control augmentation system (CAS) based on the dynamic model inversion (DMI) architecture for a highly maneuverable aircraft. In the application of DMI not treating actuator dynamics, significant instabilities arise due to limitations on the aircraft inputs, such as actuator time delay based on dynamics and actuator displacement limit. Actuator input saturation usually occurs during high angles of attack maneuvering in low dynamic pressure conditions. The pseudo-control hedging (PCH) algorithm is applied to prevent or delay the instability of the CAS due to a slow actuator or occurrence of actuator saturation. The performance of the proposed CAS with PCH architecture is demonstrated through a nonlinear flight simulation.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.169-174
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• 1999

In this paper, the CLQR(Constrained LQR) controller, which considers the actuator saturation in a cross-product term of a given performance index for an automotive active suspension control has been proposed. The effects of actuator saturations have been reflected directly in the states by using the linear relation between the control input and states. The method proposed here is more effective and intuitive compared with the conventional schemes. The CLQR has been applied to designing an automotive active suspension control system to verify its effectiveness and practical aspects.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2910-2912
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• 2000

Since the heavy-duty power manipulator has high ratio gear reducers at its joints, its dynamic characteristics are much slower than that of the master manipulator and it is likely to encounter the saturation in the input magnitude when it is used as the slave manipulator in telemanipulator systems. This paper proposes a force reflecting position control scheme for 2 axes heavy-duty power manipulator which compensates control input saturation. A series of experiments is shown to give an excellent tracking performance regardless of saturation.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.1
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• pp.22-29
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• 2008

In this paper, we propose an adaptive color enhancement algorithm. It is used for the flat panel displays (FPDs) such as LCD, PDP, and so on. The proposed algorithm consists of an adaptive linear approximation CDF(Cumulative Density Function) algorithm and an adaptive saturation enhancement algorithm. The one is for contrast enhancement which prevents an image from the distortion by luminance transient of an input image. The other is the algorithm which improves the saturation without the contour artifact and over-saturation, whose problems are generated during the enhancing saturation. In addition, it allows to achieve the high quality image using the saturation enhancement method for a preferred color of original image. Visual test and standard deviation of their histograms have been applied to evaluate the resultant output images of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.773-780
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• 1999

A digital tracking controller is proposed for micro electrostatic actuator with input nonlinearity, where disturbance observer is utilized in cooperation with inverse function. Generally the disturbance observer is announced to be robust to modeling uncertainty, and external disturbance. But, when the nonlinearity exists in the systems, the disturbance observer may not directly be applied to that system, because the nonlinearity may destabilize the overall system. Therefore, first, we linearize the nonlinear input characteristics of micro electrostatic actuator by the use of inverse function. Secondly, we apply disturbance observer to approximately linearized system for eliminating the residuals of nonlinearity and the modeling uncertainty. Then, we get the good properties of the disturbance rejection as well as the robustness due to the own nature of disturbance observer. In this case, we propose a sufficient condition for the robust stability of overall systems. Furthermore, we discuss the problem that may be exposed when disturbance observer is applied to the internally stable system with saturation, and analyze two methods to overcome input saturation problem in the sense of internal stability. Simulations have been carried out to show the effectiveness of the proposed controller.

• Steel and Composite Structures
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• v.52 no.5
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• pp.571-581
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• 2024

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. This work studies the tracking control problem of a class of strict-feedback nonlinear systems with input saturation nonlinearity. Under the framework of dynamic surface control design, RBF neural networks are introduced to approximate the unknown nonlinear dynamics. In order to address the impact of input saturation nonlinearity in the system, an auxiliary control system is constructed, and by introducing a class of first-order low-pass filters, the problems of large computation and computational explosion caused by repeated differentiation are effectively solved. In response to unknown parameters, corresponding adaptive updating control laws are designed. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.72-78
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• 2006

The paper proposes reference model error feedback control scheme for motion control system with hard non-linear components as like saturation and dead-zone in plant input part. Additionally, the plant has the system uncertainty effected by plant model parameter deviation and disturbance. The control algorithm uses the reference model to apply additional feedback loop with the error between reference model output and actual output effected by disturbance and non-linear components. And the stability evaluation based on Popov stability and controller design method are formulated to be performed. The effectiveness of the proposed scheme is examined by simulations. The results are proven by reasonable performances following reference model responses with good disturbance rejection performance without over-tuning of controller.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.325-328
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• 2002

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation is studied from an input-output feedback linearization with adaptive algorithm. The $\pi$-model of induction motor is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. Simulation results are provided for illustration.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.335-338
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• 2003

In this paper, we considered the design of gain scheduled controllers for linear systems with input constraints. The gain scheduled control is a method that uses larger control gain when the states are smaller, and smaller gain when it is larger. By doing this, we can use a full actuator capacity. Also we allow the over-saturation in control to improve the performance. First, we derive a control and a reachable set expressed as LMI form, while minimizing the $L_2$ gain from the disturbance to the measured output. Next, the reachable set is divided as nested subsets, and the control gains are obtained by minimizing the $L_2$ gain at each nested subset. Finally, the control gains are scheduled according to the status of states, i.e., the nested-subset in which the states are located. Performance of the proposed technique is illustrated through simulations of a six-story building subject to earthquake ground motion.