• Journal of Electrical Engineering and Technology
• /
• v.7 no.2
• /
• pp.240-245
• /
• 2012

A 160 MW drum-type boiler-turbine system is developed in the present research through a multi-multivariable dynamic matrix control (DMC) scheme and a multi-multivariable model approach. A novel intelligence-based decision mechanism (IBDM) is realized to support both model approach and control scheme. In such case, the responsibility of the proposed IBDM is to identify the best multivariable model of the system and the corresponding multivariable DMC scheme to cope with the system at each instant of time in an appropriate manner.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.5
• /
• pp.433-440
• /
• 2001

In this paper, we propose an automatic navigation system of ship using multivariable fuzzy control system in dynamic sea environment. The proposed multivariable fuzzy control system consists of two subsystems with three inputs and two outputs. The effectiveness of the proposed multivariable fuzzy control system is shown by simulation results.

• Journal of the Korean Society of Industry Convergence
• /
• v.9 no.3
• /
• pp.173-178
• /
• 2006

For the design of multivariable fuzzy control systems decomposition of control rules is a efficent inference method since it alleviates the complexity of the problem. In some systems, however, inference error of the Gupta's decomposition method is inevitable because of its approximate nature. In this paper we define indices of applicability which decides whether the decomposition method can be applied to a multivariable fuzzy system or not.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.490-493
• /
• 1996

This paper presents a control scheme for the motion of a 2 DOF robot manipulator. Robot manipulators are multivariable nonlinear systems. Fuzzy logic is avaliable human-like control without complex mathematical operation and is suitable to nonlinear system control. In this paper, Implementation of fuzzy logic control of robotic manipulators shows. Algorithm has been performed with simulation packages MATRIXx and SystemBuild.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.179-184
• /
• 1993

In general, for underwater vehicles in low speed, depthkeeping operations are carried out by using the variation of the weight in the seaway tank. The depthkeeping control of underwater vehicles is difficult because of the deadzone effect in the flow rate control valve. In this paper, the nonlinear multivariable QLQG/LTR control system using a seaway tank and bow planes is synthesized in order to improve the performance of the depth control system. The computer simulation results show the multivariable QLQG/LTR control system has good depth control performance under the deadzone effect.

• 전기의세계
• /
• v.31 no.4
• /
• pp.296-302
• /
• 1982

The computer algorithm and program are developed to obtain the Luenberger Canonical form and the transform matrices for linear time invariant multivariable control systems. The model controller of an eigth order system, which assigns the modes of the multivariable control systems and closed-loop matrices are computed numerically by the developed programs. It is shown that the computed results coincide with the Luenberger's and Kalman's method. The gain of the model controller has varied from 10$^{-3}$ to 10$^{5}$ by the modes assignment of the open-loop system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.5
• /
• pp.636-643
• /
• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• Nuclear Engineering and Technology
• /
• v.55 no.3
• /
• pp.850-860
• /
• 2023

An industrial control process multiple-input multiple-output (MIMO) coupled system is analyzed in this study as an example of a Loss of Coolant Accident (LOCA) simulation system. Ordinary control algorithms can complete the steady state of the control system and even reduce the response time to some extent, but the entire system still consumes a large amount of energy after reaching the steady state. So a multivariable decoupled energy-saving control method is proposed, and a novel energy-saving function (economic function, Eco-Function) is specially designed based on the active disturbance rejection control algorithm. Simulations and LOCA simulation system tests show that the Eco-function algorithm can cope with the uncertainty of the multivariable system's internal parameters and external disturbances, and it can save up to 67% of energy consumption in maintaining the parameter steady state.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.41 no.4
• /
• pp.21-28
• /
• 2004

This paper presents a direct multivariable self-tuning controller using neural network which adapts to the changing parameters of the higher order multivariable nonlinear system with nonminimum phase behavior, mutual interactions and time delays. The nonlinearities are assumed to be globally bounded, and a multivariable nonlinear system is divided linear part and nonlinear part. The neural network is used to estimate the controller parameters, and the control output is obtained through estimated controller parameter. In order to demonstrate the effectiveness of the proposed algorithm the computer simulation is done to adapt the multivariable nonlinear nonminimm phase system with time delays and changed system parameter after a constant time. The proposed method compared with direct multivariable adaptive controller using neural network.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.3
• /
• pp.257-266
• /
• 1999

The aim of this paper is to suggest a design method of the optimal multivariable $H_{\infty}$ control system using genetic algorithm (GA). This $H_{\infty}$ control system is designed by applying GA to the optimal determination of weighting functions and design parameter $\gamma$ that are given by Glover-Doyle algorithm which can design $H_{\infty}$ controller in the state space. The first method to do this is that the gains of weighting functions and $\gamma$ are optimized simultaneously by GA with tournament method. And the second method is that not only the gains and $\gamma$ but also the dynamics of weighting functions are optimized at the same time by eA with roulette-wheel method. The effectiveness of this $H_{\infty}$ control system is verified by computer simulation.