• 제어로봇시스템학회:학술대회논문집
• /
• 1995.10a
• /
• pp.51-55
• /
• 1995

An adaptive unified predictive control (UPC) algorithm is applied to a batch polymerization reactor for poly(methyl methancrylate) (PMMA) and the effects of controller parameters are investigated. Computational studies are performed for a batch polymerization system model developed in this study. A transfer function in parametric form is estimated by recursive least squares (RLS) method, and the UPC algorithm is implemented to control the reactor temperature on the basis of this transfer function. The adaptive unified predictive controller shows a better performance than the PID controller for tracking set point changes, especially in the latter part of reaction course when gel effect becomes significant. Various performance can be acquired by selecting adequate values for parameters of the adaptive unified predictive controller; in other words, the optimal set of parameters exists for a given set of reaction conditions and control objective.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.443-443
• /
• 2000

A systematic scheme is developed fer the design of new adaptive feedback linearizing controllers for nonlinear systems. The developed adaptation law estimates the uncertain time-varying parameters using the structure of diffeomorphisrn. Our scheme is applicable to a class of nonlinear systems which violates the restrictive parametric-pure-feedback condition [4]-[6].

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.7 s.178
• /
• pp.1689-1696
• /
• 2000

This paper proposes a new adaptive control scheme for flexible-link robots. A model-based nonlinear control scheme is designed based on a V-shape Lyapunov function, and then the nonlinear control i s extended to a model-based adaptive control to cope with parametric uncertainties in the dynamic model. The proposed control guarantees the global exponential or global asymptotic stability of the overall control system with all internal signals bounded. The effectiveness of the proposed control is shown by computer simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.316-321
• /
• 2003

This paper presents a design method of the wavelet neural network based controller using direct adaptive control method to deal with a stable intelligent control of chaotic systems. The various uncertainties, such as mechanical parametric variation, external disturbance, and unstructured uncertainty influence the control performance. However, the conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on direct adaptive control method with adaptive learning rates is proposed to control chaotic nonlinear systems whose mathematical models are not available. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary due to the powerful learning ability of the proposed intelligent control system. The gradient-descent method is used for training a wavelet neural network controller of chaotic systems. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with application to the chaotic systems.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.54.4-54
• /
• 2001

This paper proposes an adaptive control scheme for an autopilot design of Relaxed-Static-Stability(RSS) Missiles with saturating actuator. The feedback linearization controller eliminates nonlinear terms in RSS missile dynamics and makes the entire system linear. But modeling errors, disturbances and the nonlinear mismatch due to input constraints exert a bad influence on the performance of the feedback linearization controller Thus, first, we derive a parametric affine uncertainty model with modeling errors and disturbances. Then an adaptive control law with anti-windup scheme is developed, where the bounds of uncertainties are estimated with adaptive laws. The proposed adaptive controller can remove the bad effects of uncertainties, of disturbances, and of saturating actuator ...

• Journal of Advanced Marine Engineering and Technology
• /
• v.38 no.10
• /
• pp.1318-1326
• /
• 2014

The purpose of a tracking control system is to track a moving target and to find the exact information of the target. If the platform of the tracking control system is equipped on a moving vehicle such as a ship, the tracking control system will treat even the additional platform motion. In order to avoid the complexity comprising the tracking control system, a process to treat the platform motion, named stabilizing system, must be separated from the tracking control system. In this paper, a method to comprise an attitude control system for the platform stabilization is proposed using an adaptive fuzzy control which is applicable to the system with structural and parametric uncertainty. The suggested adaptive fuzzy control algorithm is the 2nd/1st-type indirect adaptive fuzzy control algorithm using the advantages of 1st-type and 2nd-type indirect adaptive fuzzy control algorithm. Several experiments using the implemented stabilizing system are executed for verifying the effectiveness of the suggested method.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.4
• /
• pp.612-619
• /
• 2005

A robust adaptive speed sensorless induction motor direct torque control (DTC) using a neural network (NN) is presented in this paper. The inherent lumped uncertainties of the induction motor DTC system such as parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN. An additional robust control term is introduced to compensate for the reconstruction error. A control law and adaptive laws for the weights in the NN, as well as the bounding constant of the lumped uncertainties are established so that the whole closed-loop system is stable in the sense of Lyapunov. The effect of the speed estimation error is analyzed, and the stability proof of the control system is also proved. Experimental results as well as computer simulations are presented to show the validity and efficiency of the proposed system.

• Proceedings of the KIEE Conference
• /
• 2008.04a
• /
• pp.51-52
• /
• 2008

In this paper, we propose two control schemes. The first control scheme is an adaptive passivity-based excitation control which regulates the terminal voltage to its reference. This controller is obtained through two steps: firstly, a simple direct adaptive passivation controller is designed for the power system with parametric uncertainties; then a linear PI controller is applied to converge the terminal voltage to its reference. The second control scheme is a linear governor control which consists of the frequency and the mechanical power. It is shown that the internal dynamics are locally stable with controllable damping. In the end, the boundness of all electrical variables, the frequency, the mechanical power, and the convergence of the terminal voltage to its reference can be achieved by these control schemes.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.739-744
• /
• 2004

This paper presents an adaptive approach to control the amount of slip of the torque converter bypass clutch using its estimated friction coefficient. The proposed approach can be readily implemented using the inexpensive speed sensors currently installed in an automobile. A measurement feedback control law to drive the slip error to zero together with an adaptation law to identify the unknown friction coefficient is developed using the Lyapunov control design method. The robustness of the control and adaptation laws to parametric and/or torque uncertainties as well as the convergence of the friction coefficient are investigated. Simulation results verify the viability of the proposed control algorithm in real-world vehicle control applications.

• Proceedings of the KIEE Conference
• /
• 2007.10a
• /
• pp.63-64
• /
• 2007

In this paper, an adaptive passivity based excitation and governor control scheme is proposed to enhance the transient stability of a single machine infinite bus power system with parametric uncertainties. We employ a state model where the frequency, the difference between active and mechanical power, and the difference between the squared terminal voltage and its reference are regarded as state variables. Using this state model, the proposed controller is obtained in two steps; firstly, a simple direct adaptive passivation controller is designed for the power system with parametric uncertainties; then a linear PI controller is applied to guarantee the stability of the closed loop system.