José Antonio Cortajarena

Efficient Multivariable Generalized Predictive Control for Sensorless Induction Motor Drives

This paper presents the design and the experimental validation of a new linear multivariable generalized predictive control for speed and rotor flux of induction motor. This control approach has been designed in the d-q rotating reference frame, and the indirect vector control has been employed. Load and flux observers, as well as the possibility of including a model-reference-adaptive-system speed estimator, have been considered in the implementation. The proposed controller not only provides enhanced dynamic performance but also guarantees compliance with physical voltage and current constraints. Hence, it ensures that the space vector pulsewidth modulation (SVPWM) always operates in the linear area and that the stator windings are not damaged due to overcurrent. Moreover, the controller includes a novel torque current tracker that allows obtaining an effective electromagnetic torque without a chattering phenomenon. Several simulation and experimental tests have been carried out, both in suitable and adverse conditions, even at zero speed zone, demonstrating that the proposed controller provides an efficient speed tracking and suggesting its use in industry.

Neural Network Model Reference Adaptive System Speed Estimation for Sensorless Control of a Doubly Fed Induction Generator

Abstract This article proposes a neural network model reference adaptive system for the rotor angle and speed estimation of the doubly fed induction generator used in wind turbines. The model reference adaptive system reference signal is the measured rotor current. The adaptive neural network adjusts the weights minimizing the rotor current vector squared error using the steepest descent algorithm. The neural network maximum stable learning rate will be determined for this application. The validity of the proposed neural network model reference adaptive system is verified and analyzed in a real prototype of 7.5-kW doubly fed induction generator. To validate the proposed estimator, the estimated rotor angle and speed in the process of connecting the doubly fed induction generator to the grid and the sensorless regulation according to a random wind speed profile are presented.

Indirect Vector Controlled Induction Motor with four Hybrid P+Fuzzy PI Controllers

In this paper, a new high performance induction motor drive is presented. The induction motor is controlled with four proportional plus fuzzy PI controllers (P+FUZZY PI). This hybrid controller replaces the conventional PI controllers traditionally used for indirect vector control of induction motors. The hybrid indirect vector control using the fuzzy controllers offers enhanced performance both in mathematical simulations and during actual test utilizing a 7.5 kW induction motor. The results demonstrate the superior performance and robustness of the fuzzy logic controller over the conventional controller when there are mismatched motor parameters. Notably, the performance of the fuzzy logic controller is retained when a new different motor replaces the test motor.

Effective and Robust Generalized Predictive Speed Control of Induction Motor

This paper presents and validates a new proposal for effective speed vector control of induction motors based on linear Generalized Predictive Control (GPC) law. The presented GPC-PI cascade configuration simplifies the design with regard to GPC-GPC cascade configuration, maintaining the advantages of the predictive control algorithm. The robust stability of the closed loop system is demonstrated by the poles placement method for several typical cases of uncertainties in induction motors. The controller has been tested using several simulations and experiments and has been compared with Proportional Integral Derivative (PID) and Sliding Mode (SM) control schemes, obtaining outstanding results in speed tracking even in the presence of parameter uncertainties, unknown load disturbance, and measurement noise in the loop signals, suggesting its use in industrial applications.

Sensorless induction motor parameter identification and control

In this paper, a sensorless induction motor parameter identification is presented. Sensorless control employs a variety of estimators and observers of motor speed, torque and fluxes, and accurate information about motor parameters is crucial to obtain a high performance control. The parameters of the induction motor equivalent circuit are obtained by means of DC an AC tests using the voltage-source inverter. When these parameters are estimated a closed loop flux estimator and an open loop speed estimator are implemented to determine the mechanical parameters of the machine. The parameter estimation procedure has been simulated and tested in a 7.5 kW induction motor. With the obtained parameters a sensorless control was implemented.

Speed measurement and estimation algorithms in AC Induction Motors

In this paper, the multiple period speed measurement is compared with the classical frequency and/or period methods used. The proposed speed method is used to examine the quality of the three implemented speed estimators. These estimators get the information from measured stator currents and from motor stator voltage. Open loop estimators or observers are used to estimate rotor or stator flux and rotor speed to use as feedback signals. An improved open loop estimator, an MRAS, and an EKF observer are tested utilizing a 7.5 kW induction motor. They have different accuracy, robustness and sensitivity against parameter variations and all of them have the same problem when the rotor speed is around zero.

Adaptive sliding mode control scheme for a wave power generation plant

Robust control algorithms may improve the efficiency of wave power conversion systems since they present intrinsic nonlinear dynamics and the system uncertainties. Sometimes, the generators that can operate al variable speed (e.g. double feed induction generator) are used at wave power generation plants, since they may improve the system efficiency to generate power when compared to fixed speed generators. The main reason is that this generators with variable speed may adapt the speed of the turbine in order to maintain the optimun flow coefficient value which improving its efficiency. This paper proposes a sliding mode controller for wave power plants based on a double feed induction generator. Also, the presented robust control scheme introduces an adaptive sliding gain that avoids calculating the upper bound for the uncertainties of the system, facilitating its application. The stability of the proposed control scheme is analyzed by means of the Lyapunov stability theory. Finally, the proposed control scheme is validated through some simulation examples.

Effective Proportional Derivative position control of induction motor drives

This paper presents an effective Proportional Derivative (PD) position controller of induction motor drives. A new procedure for controller design in frequency domain and the d-q synchronous rotating reference frame is presented, where the indirect vector control has been used. This position controller is validated experimentally using an industrial induction motor of 7.5 kW and an incremental encoder of 4096 impulses per revolution. The position regulator includes an effective FeedForward (FF) term instead of the Integral action (I), reducing drastically the undesirable effect of the unknown load disturbance on the position tracking. The presented algorithm has been tested using several simulation and real experiments, in suitable conditions and also in adverse conditions employing the unknown load disturbance, parameter uncertainties and measurement noise in the position and stator current loops signals, where its functional robustness is clearly demonstated. The obtained results are very satisfactory, suggesting its use in industry and in the research area to be used as a reference with other advanced position regulators. The stability of the controlled system is demonstrated in frequency domain and also by discretization of poles.

A Robust Induction Motor Control using Sliding Mode Rotor Flux and Load Torque Observers

A sliding mode position control for high-performance real-time applications of induction motors is developed in this work. The design also incorporates a sliding mode based flux and load torque observers in order to avoid this sensors, that increases the cost and reduces the reliability. Additionally, the proposed control scheme presents a low computational cost and therefore can be implemented easily in a real-time applications using a low cost DSP-processor. The stability analysis of the controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated and experimental results show that the proposed controller with the proposed observer provides a good trajectory tracking and that this scheme is robust with respect to plant parameter variations and external load disturbances.

Control and Estimation of Asynchronous Machines Using Fuzzy Logic

These techniques are traditionally solved using a mathematical model of the machine with fixed parameters. However, in a real machine, the stator and rotor resistances are altered by temperature and the inductances are altered by the magnetizing current values that change for example when the machine is running in the flux weakening region or by an improper detuning between the flux and torque producing currents. For these reasons, the induction machine shows properties of nonlinear and time-varying systems. Parameter variations degrade the system performance over the full range of motor operation and in extreme conditions this can lead to instability (Vas, 1999). To solve this problem the controller parameters have to be continuously adapted. This adaptation can be achieved using different techniques such as MRAC or model reference adaptive control (Zhen & Xu, 1998), sliding mode (Won & Bose, 1992), or self tuning PIDs (Astrom & Hagglung, 1996). For some of these techniques the motor parameters and load inertia must be calculated in real time, so there is a high processing requirement for the used processors.