Earticle

A novel fuzzy sliding-mode structure has been proposed for the model reference adaptive system(MRAS) based sensorless control of an induction motor in this paper. The design includes a hybrid MRAS from measured stator terminal voltages and currents. The estimated speed is used as feedback in an indirect vector control system achieving the speed control without using shaft mounted transducers. Fuzzy sliding-mode structure includes two nonlinear controllers, one of which is sliding mode type and the other is PI-fuzzy logic based controller, the latter define a new control structure. Both controllers are combined by means of an expert system based on Takagi-Sugeno fuzzy reasoning. The sliding mode controller acts in the steady state. The new structure has two advantages: sliding-mode controller increasing system stability and PI-like fuzzy logic based controller reducing the chattering in permanent state. The scheme has been implemented and experimentally validated.

일반적인 전동기 구동에 있어서 부하의 변화에 의해 관성이 변하는 경우 동일 속도 제어기 이득에서의 속도 응답은 오버슈트가 생기거나 진동하는 문제점이 있다. 따라서 정확한 속도제어가 필요한 응용분야에서 전동기의 관성 추정은 필수이다. 본 논문에서는 MRAS 관측기를 활용하여 영구자석동기전동기의 관성을 추정하고 추정된 관성으로 속도제어기의 제어이득을 선정할 경우의 속도 응답특성을 비교한다.

The MRAS proposed by Schauder [8] is modified to improve robustness to the change of load torque and/or the variation of the stator resistance. The difference between the voltage and the current model is fed into the current model via proportional and integral gains. In order to generalize the MRAS, supposing that the rotor speed is time varying, we add a compensating term to the current model. It does not alter the Popov's integral inequality condition. Also, the asymptotic stability of the modified MRAS (MMRAS) is shown with the stability proof technique as in the original paper. By the simulation works, it is verified that the MMRAS obtains improved performance than the original MRAS.

In this paper, simultaneous estimation of rotor speed and time constant for a voltage source inverter (VSI) fed induction motor drive are disccussed. The theory is based on the Model Reference Adaptive System (MRAS). The identifier executes Simultaneous rotor speed and time constant so that vector control of the induction may be achieved in the rotor-flux oriented reference frame. Furthermore, to eliminate the offset error caused by the change in the stator resistance, a fuzzy resistance regulator is also designed which operates in parallel with the rotor speed and time constant identifier

Precise positioning is an important problem facing motion control systems which usually use electric motor. A motor possesses a nonlinear property which degrades the positioning accuracy. Therefore, a compensator which linearizes the relationship between the angular velocity and input signal of the motor is required to enable precise positioning. In this paper, the design of a Model Reference Adaptive Control System (MRACS) for realizing the precise positioning for a system using a motor including the nonlinear property is described. The designed MRACS is applied to the attitude control problem on a satellite using a DC servomotor to drive its reaction wheel. Experimental results demonstrate the validity of a proposed control method for a positioning control system with an electric motor.

Using Power Spectrum Analysis, conditions of parameter convergence for a Model Reference Adaptive Control (MRAC) system are described. The general Persistent Excitation (PE) condition given in time domain can be transformed to the positiveness of auto-correlation matrix which is represented in frequency domain by the spectra of reference input signal. For an MRAC system designed with relative degree one, the existence and the uniqueness of parameter nominal values due to the variation of input spectra can be analyzed by the PE condition in frequency domain. If the input signal has 2n spectra or more, it can be shown that the nominal values exist independent of adaptive gain, input amplitudes, and magnitudes or numbers of their spectra.

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.

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.

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.

Related to the error dynamics of an adaptive system, averaging theorems are developed for coupled differential equations which consist of ordinary differential equations and a parabolic partial differential equation. The results are then applied to the convergence analysis of the parameter estimate errors in the model reference adaptive control of a nonautonomous parabolic partial differential equation with lowly time-varying parameters.

When the vector control, which does not need a speed? signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of flux model reference adaptive system. 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 two model are introduced to perform accurate rotor speed estimation. Simulation result show the validity of the proposed control method.

When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of Model Reference Adaptive System(MRAS). The identifier execute the rotor speed identification so that the vector control of the induc-tion motor may be achieved. The improved auxiliary variable are introduce to perform accurate rotor speed identification. Simulation and experimental result show the validity of the proposed control method.

This paper is concerned with linear system containing time delay in model reference adaptive control. An algorithm is developed using Lyapunov second method and properties of strictly positive real function.

The sliding mode control in an effective method to eatablish robustness against parameter variation and disturbance. But. In sliding mode strategy, the control function is discontinuous on the hyperplane. However the discontinuous change in control structure caves the controller input to chaffer and gives non-zero steady state error. Consequently, a multiloop feedback control system supplemented by a complelmentary controller is used to improved the drive performence of a DC servo motor and reduce sensitivity to parameter variation, nonlinear effects, and other disturbances.

This paper proposes Model Reference Adaptive Fuzzy System(MRAFS) using Fuzzy Logic Controller(FLC) as a adaptive laws in Model Reference Adaptive System(MRAS) in order to realize the speed-sensorless control of an induction motor. MRAFS estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. Fuzzy logic controller reduces the error of the rotor flux between the reference model and the adjustable model using the error and the change of error as the input of FLC. The computer simulation is executed to verify the propriety and the effectiveness of the proposed system.

In this paper model reference adaptive control (MRAC) of linear time-varying(LTV) systems is considered. MRAC for a linear time invariant(LTI) system does not assure the boundedness of the output and parameter estimation errors in the presence of time variations of the parameters. However, changing the adaptive laws such as use of $\sigma$-modification can result in the boundedness of the output and parameter estimation errors[5]. Together with the $\sigma$-modification in the adaptive law, we also modify the control law by adding an additional term to the standard control law. The additional term leads to smaller bounds of the output and parameter estimation errors when compared to the case where only the standard control law is applied.