• Transactions on Control, Automation and Systems Engineering
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• 제4권4호
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• pp.330-340
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• 2002

In this Paper. a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.

• 대한기계학회논문집A
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• 제29권1호
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• pp.88-95
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• 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.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권2호
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• pp.107-113
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• 2004

This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

• Journal of Power Electronics
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• 제13권1호
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• pp.122-138
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• 2013

Adaptive control of a peak current mode controlled (PCM) boost converter supplied by a PEM fuel cell is described in this paper. The adaptive controller with reference model and signal adaptation is developed in order to compensate the deviation of the response during the change of the operating point. The procedure for determining the adaptive algorithm's weighting coefficients, based on a combination of the pole-zero placement method and an optimization method is proposed. After applying the proposed procedure, the optimal adaptive algorithm's weighting coefficients can be determined in just a few iterations, without the use of a computer, thus greatly facilitating the application of the algorithm in real systems. Simulation and experimental results show that the dynamic behavior of a highly nonlinear control system with a fuel cell and a PCM boost converter, can fairly accurately be described by the dynamic behavior of the reference model, i.e., a linear system with constant parameters.

• 한국정보통신학회논문지
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• 제16권12호
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• pp.2708-2715
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• 2012

본 논문은 모델기준적응제어 및 직접토크제어 방식을 이용한 새로운 유도전동기의 센서리스 속도제어 방법을 제안한다. 모델기준적응제어는 기준모델과 조정모델을 설정하고 이들의 출력을 비교하여 조정모델 및 제어를 위한 속도 추정값을 얻는 제어법이다. 그리고 직접토크제어는 토크와 자속을 독립적으로 제어하는 방법으로 토크, 자속 지령치와 전동기 고정자 전압, 전류 값을 이용해 추정한 토크, 자속을 비교하여 히스테리시스 밴드를 거쳐 그 오차를 가장 최소화하기 위한 전압벡터를 선정하여 출력하는 방법이다. 본 논문에서는 제안한 방식의 이론적인 배경 및 타당성에 대해 기술하였으며 모의실험을 통해 제안된 방식의 우수성을 검증하였다.

• 전기학회논문지P
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• 제57권3호
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• pp.250-254
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• 2008

Robot actuators are significantly important with respect to whole control system performance. This paper presents an adaptive control approach for flexible robot actuators with time-varying spring and damping nature. We first represent a perturbed system model with assumption that its information are partially known. Nominal model reference control method is employed for deriving our adaptive control law. We carry out numerical simulation to evaluate the proposed control system and compare simulation results to a well-known control method for demonstrating its effectiveness.

• 한국공작기계학회논문집
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• 제12권6호
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• pp.77-83
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• 2003

This paper deals with a position control problem of a hydraulic proportional position control system using a nonlinear friction compensation control. As nonlinear friction, stiction and coulomb friction forces are considered and modeled as deadzone and external disturbance respectively. In order to compensate this nonlinearities, we designed the controller which is the adaptive friction compensator using discrete time Model Reference Adaptive Control method in this paper. Digital Signal Processing board is employed for data acquisition and manipulation. The experimental results show that response is slow and steady-state error cannot be compensated properly without friction compensation but this compensator is effective to obtain fast response and good steady-state response.

• Journal of Power Electronics
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• 제14권3호
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• pp.549-563
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• 2014

In this paper, the speed regulation problem of permanent synchronous motor (PMSM) systems under the vector control framework is studied. A model reference adaptive controller (MRAC) based on the Lyapunov stability theory is first designed. Since the standard MRAC method provides poor disturbance rejection performance in the case of strong disturbances, a composite control method which combines the MRAC method and the disturbance estimation method, called the MRAC+ESO method, is proposed. An extended state observer (ESO) is introduced to estimate the lumped disturbances. The obtained estimated value acts as a feedforward compensation term to the MRAC controller. A stability analysis of the composite control method is given. Simulation and experimental results are presented and compared to show the effectiveness of the proposed control method.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.95-105
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• 2001

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).

• 대한전자공학회논문지
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• 제26권8호
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• pp.1167-1177
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• 1989

In this paper, a generalized adaptive law is proposed which uses a rational function type operator for parameter adjustment. To satisfy the passivity condition of the adaptation block, we introduce a constant feedback gain into the adaptation block. This adaptation scheme is applied to the model reference adaptive control of a continuous-time, linear time-invariant, minimum-phase system whose relative degree is 1. We prove the asymptotic stability of the output error of this adaptive system by hyperstability method. It is shown that by digital computer simulations this law can give a better output error transient response in some cases than the conventional gradient adaptive law. And the output error responses for the several types of the proposed adaptation law are examined in the presence of a kind of unmodeled dynamics.