• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.342-345
• /
• 1996

This paper is dealing with a design of linear controller so that the plant output is regulated to follow a reference model output when the plant equation is described by a class of nonlinear time-varying control systems.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.15 no.5
• /
• pp.72-78
• /
• 2006

The paper proposes reference model error feedback control scheme for motion control system with hard non-linear components as like saturation and dead-zone in plant input part. Additionally, the plant has the system uncertainty effected by plant model parameter deviation and disturbance. The control algorithm uses the reference model to apply additional feedback loop with the error between reference model output and actual output effected by disturbance and non-linear components. And the stability evaluation based on Popov stability and controller design method are formulated to be performed. The effectiveness of the proposed scheme is examined by simulations. The results are proven by reasonable performances following reference model responses with good disturbance rejection performance without over-tuning of controller.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.2
• /
• pp.88-95
• /
• 1996

It is inevitable for local systems to have deviations which represent interactions and modeling errors originated from the decomposition process of a large scale system. This paper presents a decentralized control scheme for interconnected systems using local linear models and a neuro-coordinator. In the proposed method, the local system is composed of a linear model and unknown deviations caused by linearizing the subsystems around operating points or by estimating parameters of the subsystems. Because the local system has unmeasurable deviations we define a local reference model which consists of a local linear model and a neural network to estimate the deviations indirectly. The reference model is reformed into a linear model which has no deviations through a transformation of input variables and we obtain an optimum feedback control law which minimizes a local performance index. Finally, we derive a decentralized feedback control law which consists of local linear states and neural network outputs. In the decentralized control, the neuro-coordinator generates a corrective control signal to cancel the effect of deviations through backpropagation learning with the errors obtained from the differences of the local system outputs and reference model outputs. Also, the stability of local system is proved by the degree of learning of the neural network under an assumption on a neural network learning index. It is shown by computer simulations that the proposed control scheme can be applied successfully to the control of a biased two-link planar robot manipulator.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.228-231
• /
• 1987

Microprocessor-based software DDA interpolator is developed and applied to two axis contouring control of X-Y table. Developed assembly program is composed of feedrate, linear and circular DDA interpolation routines. Reference-pulse type of open-loop stepping motor control system in which the micro-computer produces a sequence of reference pulses for each axis of motion is adopted. To test performance of the developed program, X-Y table drive system based on stepping motor and shaft encoder is designed. Contouring error of the system in linear and circular path is within .+-.0.2 mm.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.48.2-48
• /
• 2001

This paper deals with robust integral tracking control problem based on Lyapunov method via FL(Feedback Linearization) in order to solve a reference tracking problem of nonlinear system with parameter uncertainties. To overcome a restrictive matching condition the uncertainties is characterized in a suitable form. The design procedure which combine FL and LMIs(Linear Matrix Inequalities) based on Lyapunov method to achieve the robust performance and stability is developed. Finally, the performance of proposed controller is demonstrated via simulation of a linear reference tracking problem in the MLS(Magnetic levitating System).

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.311-314
• /
• 1995

Biped locomotion can be simply modeled as a linear inverted pendulum mode. This model considers only the CG (center of gravity) of the entire system. But in real biped robot systems, the free-leg motion dynamics is not negligible. So if its dynamics is not considered in designing the reference CG motion, it is badly influence to the ZMP(zero moment point) position of the biped robot walking in the sagittal plane. Therefore, we modeled the biped locomotion similar to the linear inverted pendulum mode but considered the predetermined free-leg dynamics. To verify that the proposed biped locomotion is more stable than the linear inverted pendulum mode, we constructed a biped robot simulator and designed a serco controller to track both the reference motion of the free leg and the reference motion of CG of the biped robot using the computed torque control low. And through simulations, we verified that the proposed walking is better in stability than the one based on the linear inverted pendulum mode.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.38 no.2
• /
• pp.83-92
• /
• 1989

This paper presents a load frequency control by optimal linear tracking, which can be well adapted to practical power systems with successive load disturbances. Conventional Load Frequency Controls (LEC's) have a feedback control scheme of the state error deviated from the post-disturbance steady state. This requires the modification of reference everytime the system encounters load changes. In this study, a new feedback scheme of LEC is developed by using the optimal linear tracking method with a fixed reference. As a result, the proposed LFC, which requires no reference modification, can be efficiently applied to power systems with successive disturbances such as load changes due to the on-off operations of reclosers or feeder switches. Another feature of the proposed LFC is that it adopts an algorithm to calculate an optimal post-fault steady state with the consideration of control input changes. The proposed LFC has been tested for a 2-area power system, which shows that it can be well adapted to successive load disturbances with good frequency response.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.37 no.12
• /
• pp.884-893
• /
• 1988

Adaptive controllers for linear unknown coefficient system, that is corrupted by disturbance, are designed by parameter adaptation model reference adaptive control(MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the convergence rate of the design, an indirect-suboptimal control law is derived. Proper compensation for the effects of time-varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.37 no.10
• /
• pp.733-739
• /
• 1988

Adaptive controllers for linear system whose nominal values of coefficients only are known, that is corrupted by disturbance, are designed by signal synthesis model reference adaptive control (MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the conrergence rate of the design, an indirect suboptimal control law is de rived using the Hamilton Jacobi Beellman equation. Proper compensaton for the effects of time varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

• The Pure and Applied Mathematics
• /
• v.27 no.1
• /
• pp.35-42
• /
• 2020

In this paper, numerical algorithms for solving a fuzzy system of linear equations with crisp coefficients are presented. We illustrate the efficiency and accuracy of the proposed methods by solving some numerical examples. We also provide a graphical representation of the fuzzy solutions in three-dimension as a visual reference of the solution of the fuzzy system.