**5. Conclusions**

14 Induction Motor

(c) Simulation results for a 50 Nm trapezoidal load

Figure 7 (a) shows simulation results for a 200 revolutions per minute (rpm) trapezoidal

represent quantities in the stationary frame reference of the stator currents. The measurement speed is fed back in the closed loop for speed regulation and a PI controller is used in the speed regulation loop as shown in Figure 6. The predicted stator current in the *α* component is shown in the upper side (zoom graph, red curve). Under these test conditions, the MSE in the speed and current tracking are 0.75 rpm and 0.15 A, respectively. Figure 7 (b) shows the step response for the induction machine to a change of ±2.5 A in the current

simulation results, the subscripts (*α* − *β*) represent the stator current in stationary reference frame. Under these test conditions, the MSE in the stator current tracking are 0.1 A for the

shows a trapezoidal load application response, and the rotor current evolution (measured and observed) in stationary reference frame. These simulation results substantiate the expected

∗

*ds*) and 0.18 A considering stationary reference frame. Finally, Figure 7 (c)

*ds* = 1 A). The subscripts (*α* − *β*)

*<sup>r</sup>* = 200 rpm). In these

**Figure 7.** Simulation results for a proposed speed control. The predicted stator current in the *α*

*ds* see Figure 6), if we consider a fixed speed reference (*ω*<sup>∗</sup>

component is shown in the upper side (zoom graphs, red curves)

speed reference, if we consider a fixed current reference (*i*

(b) Simulation results for a ±2.5 A step in the reference

current comand tracking

(a) Simulation results for a ±320 rpm step wave speed

comand tracking

reference (*i*

∗

∗

reference current (*i*

In this chapter a new approach for the speed control of the asymmetrical dual three-phase induction machine has been proposed and evaluated. The speed control scheme uses an inner loop predictive current control based on the model, where the main advantage is the absence of modulation techniques. The MBPC is described using a state-space representation, where the rotor and stator current are the states variables. The proposed algorithm provides an optimal estimation of the rotor current in each sampling time in a recursive manner, even when internal parameters of the drive are not precisely known, and the measurements of the state variables are perturbed by gaussian noise. The theoretical development based on a Kalman Filter has been validated by simulations results. The method has proven to be efficient even when considering that the machine is operating under varying load regimes.
