Adaptive Input–Output Feedback-Linearization-Based Torque Control of Synchronous Reluctance Motor Without Mechanical Sensor

In this paper, a well-known adaptive input-output feedback-linearization (AIOFL) technique is used for speed and torque-tracking control of synchronous reluctance motor drive. This controller is capable of estimating motor two-axis inductances (
Ld
,
Lq
) simultaneously. The overall stability of the proposed control and the persistency of excitation condition are proved based on Lyapunov theory. In addition, the maximum rate of change of torque control scheme is applied to generate the motor
d
- and
q
-axis reference currents which are needed for AIOFL controllers. Another contribution of this paper is to estimate the rotor speed and position. For low-speed estimation, we have to eliminate the current and voltage sensors' dc offsets, detect the stator resistance, and take into account the voltage drop of the inverter power switches. We solve these problems by using a simple technique for eliminating the voltage sensors and a simple method for online estimation of the stator resistance and modeling the voltage drop of the inverter power switches. It is worthwhile to mention that the current sensors' dc offsets, seen on the measured currents, are negligible. Finally, the validity of the proposed method is verified by experimental results.