Robust Control of Sensorless AC Drives Based on Adaptive Identification

Abstract

In most of the modern drive systems with alternating current (AC) machines which require rotor speed control, the main task is to design and develop different controllers, able to achieve high dynamic performance and to maintain the system response within specified tolerances, for a wide range of speed and torque values, for parameter variations and for external perturbations like: total inertia moment, friction coefficient, etc. (Leonhard, 1985). Various concepts for controlled AC drives without speed sensor (sensorless control) have been developed in the past few years (Holtz, 2002; Rajashekara et al., 1996; Vas, 1998). Ongoing research has focused on providing sustained operation at high dynamic performance at very low speed, including zero speed and zero stator frequency (Akatsu & Kawamura, 2000; Holtz & Quan, 2002; Hurst et al., 1998; Lascu et al., 2005). In speed sensorless control, motor parameter sensitivity is an important and large discussed and analyzed problem (Akpolat et al., 2000; Toliyat et al., 2003). In many existing speed identification algorithms, the rotor speed is estimated based on the rotor flux observer. Therefore, these algorithms are, to a certain degree, machine parameter dependent. The solution proposed in this chapter is to apply robust control to sensorless AC drive systems. The designing procedure of the speed controllers can be very difficult, if a complex mathematical model of the plant (here of the AC machine) is used. But robust controllers keep the dynamic and stability performance of the controlled system even if structured or unstructured uncertainties appear. That's why, robust speed controllers can be designed by using simplified models of the AC machines, and have to be used in a complex structure based on the field-oriented control (FOC) principle (Birou & Pavel, 2008). Thus, the requirements of a digital control application are: a flexible control structure, reduced hardware configuration and a good dynamic behavior of the controlled process. The last two aspects can be realized by finding a compromise between the reducing of the control cycle times and the increasing of controller complexity. For industrial applications the hardware costs are also important. Two different algorithms will be presented to estimate the rotor speed in this chapter, one based on the model reference adaptive system (MRAS) and the other on a full order observer (FOO). The speed identification algorithms, the designing procedure of the optimal H controller and the robust control of the sensorless driving system will be accomplished by simulated and experimental results. Based on the results obtained, advantages and disadvantages of the proposed control structures will be discussed.