• 전기의세계
• /
• v.36 no.7
• /
• pp.486-490
• /
• 1987

본고에서는 현재까지 확립된 적응제어의 설계이론 특히 기준모델형 적응제어에 중점을 두고 소개하였으며, 최근에 활발하게 연구가 진행되고 있는 강인성(robustness)해석 및 개선 즉 위에서 언급한 제약을 풀어 나가기 위한 시도들의 일부에 대하여 기술하였다.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.5
• /
• pp.92-99
• /
• 1997

A model reference adaptive control(MRAC) theory is very useful for controlling a plant of which the parameters are unknown or vary during operation usint only input-output signal of plant. In this study, 2' nd order discreter time MRAC controller is designed for an electrohydraulic position control system which is represented with nonlinear mathematical model and the least square method is adopted for the para-meter adjustment law. This control algorthm is applied to the position control of electrohydraulic servosystem through computer simulation and the effect of the change of load, sampling time upon the performance following reference model and upon the performance of estimating plant parameters are examined.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.22 no.6
• /
• pp.89-96
• /
• 1985

A pole-placement control of discrete, deterministic, single-input single-output nonmini-mum phase systems is considered using a model reference type approach. The proposed pole-placement controller is designed in the parameter form to make the transfer function of the controller equal to that of the reference model with only single variable polynomial S(q-1). The proposed adaptive pole-placement controllr is designed with the true system para-meters by applying the adaptation method to the proposed pole-placement controller.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.32 no.11
• /
• pp.394-403
• /
• 1983

This paper discusses a model reference adaptive control for a multi-input multi-output continuos system in matrix fraction description. The controller is of Monopoli-Narendra type with a time-varying gain matrix in the parameter adaptation law. The transfer matrix of the given plant with an adjustable controller is made to approach to that of the reference model asymptotically. It is shown that, under some plausible assumptions such as on the knowlidge of an interactor matrix, the algorithm for a single-input single-output system can be appropriately extended to a multi-input multi-output system. The convergence of an adaptation law is estavlished with some stability theory and stability of the overall system is asserted by an analytical investigation.

• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.11
• /
• pp.151-157
• /
• 2000

The MRAC theory has proved to be one of the most popular algorithms in the field of adaptive control, particularly for practical application to devices such as an hydraulic servosystem of which parameters are unknown or varying during operation. For small sampling period, the discrete time system becomes a nonminimal phase system. The $\delta$-MRAC was introduced to obtain the control performance of nonminimal phase system, because the z-MRAC can not control the plant for small sampling period. In this paper, $\delta$-MRAC is applied to the control of an hydraulic servosystem which is composed of servovalve, hydraulic cylinder and inertia load.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.6 no.2
• /
• pp.97-105
• /
• 1996

In this paper, an adaptive model predictive controller for nodinear processes using fuzzy model is proposed. Adaptive structure is implemented by recursive fuzzy modeling. The model and control law can be obtained the same as GPC, because the consequent parts of the fuzzy model comprise linear equations of input and output variables. The proposed Adaptive fuzzy model predictive controller (AFMPC) controls nonlinear process well due to the intrinsic nonlinearity of the fuzzy model. When AFMPC's output is variation in the process control input, it maintains zero steady-state offset for a constant reference input and has superior performance. The properties and performance of the proposed control scheme were examined with nonlinear plant by simulation.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.1 s.232
• /
• pp.88-95
• /
• 2005

This paper presents a design scheme of model reference adaptive control incorporating a Neural Network for a pneumatic servo system. The parameters of discrete-time model of plant are estimated by using the recursive least square method. Neural Network is utilized in order to compensate the nonlinear nature of plant such as compressibility of air and frictions present in cylinder. The experiment of a trajectory tracking control using the proposed control scheme has been performed and its effectiveness has been proved by comparing with the results of a model reference adaptive control.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.4
• /
• pp.309-318
• /
• 1991

In this paper, the integrator used to reduce the error between the reference signal and response, and DC motor are constructed by bond graph. Then the model following servo controller which have the high adaptation with respect to inertia, disturbance and/or load variation in the speed control system of DC motor is designed by the bond graph, and then the usefullness of this modeling method is confirmed in operating analysis and design on controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.193-197
• /
• 1987

Decentralized model reference adaptive controller is used to control interconnected system. Influences caused by interactions between each subsystem are regarded as unmodeled dynamics or disturbances, thus decentralized adaptive controller is designed using MRAC algorithms which guarantees robustness. To expand the stability regions of over all system and to improve control performances, higher level controller is introduced to adjust the control factors such as filter band, size of deadzone or maximum norm of parameter. Local controllers for each subsystem are realized in real time and higher level controller has an ability of detecting the instability phenomena and adjusts the local controller by analysis of power spectrum or square sum of tracking errors.

• Journal of Advanced Navigation Technology
• /
• v.17 no.3
• /
• pp.332-345
• /
• 2013

In this paper, recently, it is described to the piezoelectric transformer technology develops, because it was have to favorable characteristics such as electromagnetic-noise free, compact size, higher efficiency, and superior power density, flux linkage, noiseless, etc. its resonance frequency was used to output waveform of a sine wave. A rotor speed identification method of induction motor based on the theory of flux model reference adaptive system(FMRAS). The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the model are introduced to perform accurate rotor speed estimation. The control system is composed of the PI controller for speed control and the current controller using space voltage vector PWM techniuqe and DC-DC converter. High speed calculation and processing for vector control is carried out by digital signal one chip microprocessor. Validity of the proposed control method is verified through simulation and experimental results.