• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2006.11a
• /
• pp.359-362
• /
• 2006

This study develops an automatic berthing control algorithm for ships with a bow thruster and a stern thruster as well as a rudder. A nonlinear mathematical model for low speed maneuvering of ships is used to develop a MIMO(multi-input multi-output) nonlinear control algorithm. The algorithm consists of two parts, which are forward velocity control and heading angle control. The control algorithm is designed based on the longitudinal and yaw dynamic models of ships. The desired heading angle is obtained by the so called "Line of Sight" method. An optimal control force allocation method of the rudder and the thrusters is suggested. The nonlinear control algorithms are tested by numerical simulations using MATLAB, and shows good tracking performances.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.588-588
• /
• 1991

This paper proposes a compliance robot control algorithm using fuzzy adaptive controller and fuzzy compliance vector generator. In the compliance robot control, we need more adaptivity because the linear modeling in robot dynamics is getting more difficult by contact with external environment. Existing adapitive controllers have difficulty in realtime processing. So in order to overcome it, We adopt fuzzy adaptive controller and propose fuzzy compliance vector generator for flexible compliant motion. We analyze and confirm the proposed algorithm by surface processing experiment with a control system implemented by VME system.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2003.04a
• /
• pp.193-200
• /
• 2003

This paper presents a hybrid (i.e., integrated passive-active) system for seismic response control of a cable-stayed bridge. Because multiple control devices are operating, a hybrid control system could alleviate some of the restrictions and limitations that exist when each system is acting alone. Lead rubber bearings are used as passive control devices to reduce the earthquake-induced forces in the bridge and hydraulic actuators are used as active control devices to further reduce the bridge responses, especially deck displacements. In the proposed hybrid control system, a linear quadratic Gaussian control algorithm is adopted as a primary controller. In addition, a secondary bang-bang type (i.e., on-off type) controller according to the responses of lead rubber bearings is considered to increase the controller robustness. Numerical simulation results show that control performances of the hybrid control system are superior to those of the passive control system and slightly better than those of the fully active control system. Furthermore, it is verified that the hybrid control system with a bang-bang type controller is more robust for stiffness perturbation than the active controller with μ-synthesis method and there are no signs of instability in the overall system whereas the active control system with linear quadratic Gaussian algorithm shows instabilities in the perturbed system. Therefore, the proposed hybrid protective system could effectively be used to seismically excited cable-stayed bridges.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.75.5-75
• /
• 2001

In this paper, we study design of a ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between stands plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. A Looper servo controller is designed by ILQ control theory which is an inverse problem of LQ(Linear Quadratic optimal control) control. The mathematical model for looper system is obtained by Taylor´s linearization of nonlinear differential equations. Then we designed linear controller for linearization model by using the ILQ control algorithm. Thereafter this controller is applied to the nonlinear model for model identification. As a result, we show the controller´s robustness for the model error, external disturbance and sensor noise.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.215-218
• /
• 1997

A dynamic back-propagation neural network is addressed for adaptive neural control system to approximate non-linear control system rather than static networks. It has the capability to represent the approximation of nonlinear system without mathematical analysis and to carry out the on-line learning algorithm for real time application. The simulated results show fast tracking capability and adaptive response by using dynamic back-propagation neurons.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.1
• /
• pp.11-15
• /
• 1999

In this paper, a robust pole placement controller for time invariant linear systems with polytopic uncertainties is presented. The proposed controller is a fixed order output feedback controller which stabilizes the uncertain systems and satisfies the constraints on the closed-loop pole location. The proposed controller can be obtained by minimizing a certain nonlinear object function subject to linear matrix inequality constraints. An algorithm for solving the nonlinear optimization problem is also proposed.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.856-861
• /
• 1989

The control of a class of large scale systems formed by an arbitrary linear interconnections of linear time-invariant subsystems with unknown parameters is investigated. An approach is developed for improving the robustness of such a large scale system. In doing so, the new parameter adaptation algorithm(PAA) is used and a sufficient condition of stability is discussed by using the sector theory.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.21 no.6
• /
• pp.135-146
• /
• 2013

This paper presents a feedforward control algorithm for the EGR and VGT systems of passenger car diesel engines. The air-to-fuel ratio and boost pressure are selected as control indicators and the positions of EGR valve and VGT vane are used as control inputs of the EGR and VGT controller. In order to compensate the non-linearity and coupled dynamics of the EGR and VGT systems, we have proposed a non-linear model-based feedforward control algorithm which is obtained from static model inversion approach. It is observed that the average modeling errors of the feedforward algorithm is about 2% using stationary engine experiment data of 225 operating conditions. Using a feedback controller including proportional-integral, the modeling error is compensated. Furthermore, it is validated that the proposed feedforward algorithm generates physically acceptable trajectories of the actuator and successfully tracks the desired values through engine experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.4
• /
• pp.198-204
• /
• 2003

In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on two steps. The first step transforms nonlinear optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPBCP(two point boundary condition problem) is solved by algebraic equations instead of differential equations using the new integral operational matrix of BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems and is less error value than that by the conventional matrix. In computer simulation, the algorithm was verified through the optimal control design of synchronous machine connected to an infinite bus.

• Proceedings of the KIEE Conference
• /
• 2005.05a
• /
• pp.119-121
• /
• 2005

The sliding-mode control technique could make a system unstable which external disturbance and uncertainty exists in. This paper suggests a robust sliding-mode control algorithm which can be applied to a linear system with parameter uncertainties. To reduce the chattering effect, the whole system is comprised of using a state variable in which the state's estimated value is added. The condition of estimated state results from state observer. The proposed control algorithm uses the optimal feedback controller following the dynamic system equation which consists of a state variable resulting from its own state variable, controller input, estimated state variable. Through comparison with the time optimal control algorithm using simulation, the suggested algorithm shows the improved stability and robustness while it manifests the fast tracking characteristics.