**8.3. Classical and Robust estimators under PMSM parameters variation**

The simulation results below presents the DTC for PMSM performances in case of speed PI controller and Robust estimator, and speed FLC and this estimator under motor parameters variation, which are stator resistance, friction coefficient and motor inertia. Figure 37 (on the left) shows the variations, of these three parameters, applied to examine DTC robustness: the stator resistance was changed from the nominal value 1.59 Ω to the double of this value 3.18 Ω, the friction coefficient was changed from the nominal value f=0.00047 Nm.s/rd to f1=100\*f and the motor inertia was changed from the nominal value J=0.003573 Kg.m2 to J1=100\*J.

It's seen in figure 37 (on the right) that the speed FLC allows to achieve a faster response and reject the perturbations (motor parameters variations), whereas the speed PI controller takes much time, in comparison with FLC, to reject these perturbations. Also, a faster motor torque response has been achieved with speed FLC compared to speed PI controller; as shown in figure 38 (on the left). Indeed, combining speed FLC and the novel estimator allow DTC for PMSM to reject stator resistance variation thanks to this estimator and reject motor inertia and friction coefficient thanks to speed FLC, which is shown in figure 38 (on the right).

**Figure 37.** PMSM parameters variation (on the left) and rotation speed evolution (on the right) in case of DTC for PMSM drive using speed PI controller and novel estimator (green color), and speed FLC and novel estimator (red color)

Improved DTC Algorithms for Reducing Torque and Flux Ripples of PMSM Based on Fuzzy Logic and PWM Techniques 193

**Figure 38.** Motor torque (on the left) and stator flux (on the right) in case of DTC for PMSM drive using speed PI controller and novel estimator (green color), and speed FLC and novel estimator (red color)
