• Structural Engineering and Mechanics
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• v.49 no.6
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• pp.687-703
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• 2014

This paper develops a new nonlinear model for active control of three-dimensional (3D) irregular building structures. Both geometrical and material nonlinearities with a neuro-controller training algorithm are applied to a multi-degree-of-freedom 3D system. Two dynamic assembling motions are considered simultaneously in the control model such as coupling between torsional and lateral responses of the structure and interaction between the structural system and the actuators. The proposed control system and training algorithm of the structural system are evaluated by simulating the responses of the structure under the El-Centro 1940 earthquake excitation. In the numerical example, the 3D three-story structure with linear and nonlinear stiffness is controlled by a trained neural network. The actuator dynamics, control time delay and incident angle of earthquake are also considered in the simulation. Results show that the proposed control algorithm for 3D buildings is effective in structural control.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1047-1052
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• 2008

In this paper, we design an image-based robust controller to compensate uncertainties with image Jacobian and robot dynamics due to uncertain depth measurement and load variations. The proposed controller with eye-in-hand structure has separate terms to compensate each of uncertainties. The ultimate boundedness of the closed-loop system is proved by the Lyapunov approach. The performance of the proposed control system is demonstrated by simulation and experimental results a 5-link robot manipulator with two degree of freedom.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.89-91
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• 2005

In this paper, we propose a robust visual feedback controller with integral action for tracking control of n-link robot manipulators in the presence of constant bounded parametric uncertainties. The proposed control input has robustness to the parametric uncertainty and reduces tracking error in the steady-state. The stability of the closed-loop system is shown by Lyapunov method. The effectiveness of the proposed method is shown by simulation results on the 5-link robot manipulators with two degree of freedom.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.107-108
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• 2006

This paper presents the design of a night vision system for vessels. Both a hardware system and software modules for stabilization control are developed. In order to stabilize each control axis, the two-degree of freedom(TDF) PID controller is designed and its parameters are tuned using a real-coded genetic algorithm(RCGA). Simulation demonstrates the effectiveness of the proposed system.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.917-922
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• 2008

In order to reduce energy consumption, secondary controlled system has been applied to many types of equipments. In lifting equipments or press machines using hydraulic cylinder, a hydraulic transformer is used as a control component instead of a valve for motion control and a component for recovering potential energy of load. The transformer is combination of a variable displacement pump/motor as a secondary controlled element and a fixed displacement pump/motor. Based on the nominal model derived from mathematical model, the feedback type two-degree-of-freedom controller is designed and implemented. From simulation results, the disturbances including nonlinear friction torque, leakage flow and load force can be compensated and good positioning accuracy is obtained. It show that the proposed controller is effective.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.199-202
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• 1995

In the conventional $H_2$ design of PI controllers, the quadratic cost function includes only the plant output term and hence, the optimal controller often results in a very large plant input. In this paper, $H_{\infty}$ design methodology is combined with the conventional $H_2$ design to make a trade-off between the regulation of the plant input and the plant output in a systematic way.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.190-194
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• 2013

This paper presents experimental results of the attitude control for a two-rotor system with 3-DOF(degree-of-freedom). Two DC motors are equipped at the two ends of a rectangular beam to generate lift force and the relation between motor voltage and lift force is found experimentally. And inertial sensors are mounted at the center of the beam to measure the roll angle and a complementary filter is designed to get the angle during DC motors driving. A controller with nonlinear compensation, integrator and state feedback to achieve asymptotic tracking for a step input and reject input disturbance is designed and experimented.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.693-697
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• 1989

In this paper, force control for a multi-legged walking robot is investigated. For stable but relatively rapid walking, a simple force control algorithm is proposed in conjunction with the position control system. The proposed control method is tested on an experimental one leg system of two degree of freedom with a force controller using a position controller and a monoboard microcomputer to implement the proposed control algorithm. The experimental results shows that the control algorithm can be applied for walking in a terrain with wide range variation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.4-41
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• 2001

In this paper, we propose a LQR(Linear Quadratic Regulator) controller design for the active suspension using two-degree-of-freedom quarter-car model. We can improve the inherent suspension problem, the tradeoff between ride quality and suspension travel by selecting appropriate weights in the LQR-objective function. Because any definite rules for selecting weights do not exist, we replace the designer´s trial and error with the optimization-algorithm, ES(Evolution Strategy). Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle´s state variables.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.168-175
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• 1999

Unlike a general inverted pendulum system which is moved on the cart the proposed inverted pendulum system in this paper has an inverted pendulum which is moved on the two-degree-of-freedom parallelogram link. The dynamic equation of the pendulum system activated by the DD(Direct Drive)motor includes many nonlinear terms and has the high degree of freedoms. The problem is followed hat the exact mathmatical equations can not be analized by a general linear theory However the neural network trained by a simple learning method can control the dynamic system with hard nonlinearities. Learning procedure is the backpropagation algorithm with super-visory signal. The plant inputs obtained by the designed neural network in this paper can stabilize the pendu-lem and get the servo control. Experiment results have proce the effectiveness of the designed neural network controller.