• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.94-101
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• 1996

The equations of motion for a basic industrial robotic system which has a rigid or a flexible arm are derived by Lagrange's equation, respectively. Especially, for the deflection of the flexible arm, the assumed mode method is employed. These equations are highly nonlinear equations with nonlinear coupling between the variables of motion. In order to design the control law for the rigid-arm robot, Hunt-Su's nonlinear transformation method and Marino's feedback equivalence condition are used with linear quadratic regulator(LQR) theory. The control law for the rigid-arm robot is employed to input the desired path and to provide the required nonlinear transformations for the flexible-arm robot to follow. By using the implicit Euler method to solve the nonlinear equations, the comparison of the motions between the flexible and the rigid robots and the effect of flexibility are examined.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.346-352
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• 1998

In this paper, we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastic approximation method, it is regarded as a stochastic recursive filter algorithm. In addition, we provide a filtering and control condition for a stochastic nonlinear system, called perfect filtering condition, in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence, the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable. and the proposed neural controller is more efficient than the conventional LQG controller and the canoni al LQ-Neural controller.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2187-2195
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• 2018

In order to realize the multi-objective control of single-input multi-output nonlinear differential algebraic system (NDAS) and to improve the dynamic characteristics and static accuracy, a design method of nonlinear control with multi-objective feedback (NCMOF) is proposed, the principium of this method to arrange system poles, as well as its nature to coordinate dynamic characteristics and static accuracy of the system are analyzed in detail. Through NCMOF design method, the multi-objective control of the system is transformed into linear space, and then it is effectively controlled under the nonlinear feedback control law, the problem to balance all control objectives caused by less input and more output of the system thus is solved. Applying NCMOF design method to generator excitation system, the nonlinear excitation control law with terminal voltage, active power and rotor speed as objective outputs is designed. Simulation results show that NCMOF can not only improve the dynamic characteristics of generator, but also damp the mechanical oscillation of a generator in transient process. Moreover, NCMOF can control the terminal voltage of the generator to the setting value with no static error under typical disturbances.

• Journal of Ocean Engineering and Technology
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• v.22 no.3
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• pp.34-40
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• 2008

his study discusses the design of an automatic berthing control algorithm for ships with a haw thruster and a stern thruster, as well as a rudder. A nonlinear mathematical model for the law speed maneuvering of ships was used to design a MIMO (multi-input multi-output) nonlinear control algorithm. The algorithm consists of two parts, the forward velocity control and heading angle control. The control algorithm was designed based on the longitudinal and yaw dynamic models of ships. The desired heading angle was obtained by the so-called "Line of Sight" method. An optimal control force allocation method forthe rudder and the thrusters is suggested. The nonlinear control algorithm was tested by numerical simulations using MATLAB, and showed good tracking performance.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.173.4-173
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• 2001

This paper presents a stable nonlinear adaptive control for AUV(Autonomous Underwater Vehicle) by using neural network. AUV's dynamics are highly nonlinear, and their hydrodynamic coefficients vary with different operational conditions. In this paper, the nonlinear uncertainties of the AUV's dynamics are approximated by using LPNN(Linearly parameterized Neural Network). The presented controller is consist of three parallel terms; linear feedback control, sliding mode control, and adaptive control(LPNN). Lyapunov theory is used to guarantee the stability of tracking errors and neural network´s weights errors. Numerical simulations for nonlinear control of the AUV show the effectiveness of the proposed techniques.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.76.3-76
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• 2002

The purpose of this paper is to present a new nonlinear feedback control called AACC (Augmented automatic choosing control) for nonlinear systems. Generally, it is easy to design the optimal control laws for linear systems, but it is not so for nonlinear systems, though they have been studied for many years. One of most popular and practical nonlinear control laws is synthesized by applying a linearization method by Taylor expansion truncated at the first order and the linear optimal control method. This is only effective in a small region around the steady state point or in almost linear systems. Controllers based on a change of coordinates in differential geometry are effective in wider...

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.356-366
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• 2000

In this paper, a nonlinear $H_2/H_\infty/LTR$ control for the flexible inverted pendulum of a parallel type with Coulomb friction is presented. The dynamic equation for this system is derived by the Hamilton's principle and assumed-mode method. This hard nonlinear system can be modeled by a the quasi-linear state space model using the REF method. It is shown that the $H_2/H_\infty$ control can be applied to the nonlinear controller design of the system having Coulomb frictions if the proper LTR conditions are satisfied. In order to present the usefulness of the suggested control method, the nonlinear $H_2/H_\infty/LTR$ controller is designed to control the Position of the end point of the flexible inverted pendulum that has Coulomb frictions present in actuator parts. The results are given via computer simulations.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.85-89
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• 1998

A switching power stage is a very nonlinear system because it has two or more operation modes in one switching cycle. To model a switching power stage, the state space averaging method has been developed. Though it allows a unified treatment of a large variety of switching power stages, the model it yields is always very nonlinear. So, it is required to linearize the averaged model. But it is well known that a controller for a nonlinear plant designed by the linearization frequently fails in showing satisfactory control performance. Hence it is very natural to try to design a nonlinear controller for a switching power stage. In design of a switching power system, nonlinear control approaches such as adaptive control and fuzzy control have been widely studied so far. In this research, a recently developed control method, time delay control is briefly studied and a design example for a ZVS PWM half bridge converter is given. The performance of the time delay controller is compared to its conventional counterpart, PI controller by computer simulations.

• 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.

• Structural Engineering and Mechanics
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• v.83 no.1
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• pp.31-43
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• 2022

A nonlinear gas-spring tuned mass damper is proposed to mitigate the seismic responses of the multi-degree-of-freedom (MDOF) structure, in which the nine-story benchmark model is selected as the controlled object. The nonlinear mechanical properties of the gas-spring are investigated through theoretical analysis and experiments, and the damper's control parameters are designed. The control performance and damping mechanism of the proposed damper attached to the MDOF structure are systematically studied, and its reliability is also explored by parameter sensitivity analysis. The results illustrate that the nonlinear gas-spring TMD can transfer the primary structure's vibration energy from the lower to the higher modes, and consume energy through its own relative movement. The proposed damper has excellent "Reconciling Control Performance", which not only has a comparable control effect as the linear TMD, but also has certain advantages in working stroke. Furthermore, the control parameters of the gas-spring TMD can be determined according to the external excitation amplitude and the gas-spring's initial volume.