Speed Sensorless Induction Motor Research Articles

Performance analysis of a speed-sensorless induction motor drive based on a constant-switching-frequency DTC scheme

A control technique, which utilizes the stator flux components as control variables, has been applied to a speed-sensorless induction motor drive. The scheme may be regarded as a development of a direct torque control scheme, aimed at achieving a constant-switching-frequency operation. At each sampling period the required voltage vector is calculated on the basis of the error between the reference and the estimated stator flux vector. The problems related to the voltage-source inverter dead time and the stator flux estimation at low speed have been analyzed, and an efficient solution has been proposed. The performance of the drive system has been verified by experimental tests, and good results have been achieved in both steady-state and transient operating conditions.

Hybrid control for speed sensorless induction motor drive

The dynamic response of a hybrid-controlled speed sensorless induction motor (IM) drive is introduced. First, an adaptive observation system, which comprises speed and flux observers, is derived on the basis of model reference adaptive system (MRAS) theory. The speed observation system is implemented using a digital signal processor (DSP) with a high sampling rate to make it possible to achieve good dynamics. Next, based on the principle of computed torque control, a computed torque controller using the estimated speed signal is developed. Moreover, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a recurrent fuzzy neural network (RFNN) uncertainty observer is utilized to adapt the lumped uncertainty online. Furthermore, based on Lyapunov stability a hybrid control system, which combines the computed torque controller, the RFNN uncertainty observer and a compensated controller, is proposed to control the rotor speed of the sensorless IM drive. The computed torque controller with RFNN uncertainty observer is the main tracking controller and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer instead of increasing the rules of the RFNN. Finally, the effectiveness of the proposed observation and control systems is verified by simulated and experimental results.

A novel stator resistance estimation method for speed-sensorless induction motor drives

A method for online estimation of the stator resistance of an induction machine is presented and a speed-sensorless field-oriented drive equipped with the proposed estimator is built. The drive is particularly suitable for low-speed operation. Resistance estimation is based on a two-time-scale approach, and the error between measured and observed current is used for parameter tuning. The simple full-order observer in use allows for direct field orientation in a wide range of operation. The system can drive active load and generate stall torque, as confirmed by numerical simulations and experimental tests on a general-purpose 7.5 kW induction machine.

Robust speed sensorless induction motor drive

A speed sensorless induction motor (IM) drive with robust control characteristics is introduced. First, a speed observation system, which is insensitive to the variations of motor parameters, is derived based on the concept of sliding mode. Next, an integral-proportional (IP) speed controller using the estimated speed signal is designed to stabilize the speed loop. Then, to preserve the robust control performance under parameter variations and external load disturbance, an adaptive uncertainty observer with feedforward control is proposed. The adaptive uncertainty observer is implemented to estimate the lump of uncertainty of the controlled plant. To increase the accuracy of the estimated values, the speed observation system is implemented using a digital signal processor (DSP) with a high sampling rate.

DSP-based minmax speed sensorless induction motor drive with sliding mode model-following speed controller

A speed sensorless induction motor (IM) drive with a sliding mode model-following speed controller is introduced. First, the speed estimation algorithm, based on the minmax control theory, and its stability analysis are described. An integral-proportional (IP) speed controller using the estimated speed signal is designed to obtain the desired control performance of command tracking. Moreover, to increase the robustness of the IM drive, a sliding mode model-following controller is added, where the state-space equation of the nominal designed IP speed control loop is selected as the reference model. To increase the accuracy of the estimator, the speed estimation algorithm is implemented using a digital signal processor.

ROTOR RESISTANCE ESTIMATION FOR SLIP ADAPTATION IN SENSORLESS INDUCTION MACHINE DRIVES

ABSTRACT This work presents a rotor resistance estimation algorithm. The estimation process is based on a recursive least squares method. It is applied to a speed sensorless induction motor drive scheme in order to implement slip adaptation. A discrete approach is considered in which an induction motor model written in form of difference equations is used by the estimation algorithm. All the associated mathematical developments are shown. Simulation results are used to verify the performance of the proposed rotor resistance estimator.

A comparative study of sliding mode and model reference adaptive speed observers for induction motor drive

A comparative study of sliding mode and model reference adaptive speed observers for a speed sensorless induction motor (IM) drive is introduced in this paper. First, a speed observer on the basis of the sliding mode control theory is proposed. Then, the sliding mode speed observer is compared with the speed estimation algorithm based on model reference adaptive system (MRAS) theory to verify the robustness against parameter variations. An integral proportional (IP) speed controller using the estimated speed signal is designed to stabilize the speed loop. Moreover, to increase the accuracy of the estimated speed, the speed estimation algorithms are implemented using a digital signal processor (DSP). The effectiveness of the proposed sliding mode speed observer is demonstrated by some simulation and experimental results.