*6.2. Practical Results*

Figure 13 shows the experimental setup for the configured drive system. The drive system includes an induction motor; with the same parameters and data specification of the induction motor which used for simulating the proposed control scheme; linked with a digital control board (TMDSHVMTRPFCKIT from Texas Instruments with a TMS320F28035 control card) [32,35]. The complete control scheme has been programmed in the package of Code Composer Studio CCS from Texas Instruments.

**Figure 13.** A photo of the experimental setup for induction motor drive.

To validate the effectiveness of the sensorless vector control of the induction motor drive, the experiments were accomplished at different values of the reference speed. Figures 14–16 show samples of the results when the proposed system is tested at reference speeds of 0.2 pu and 0.4 pu; the base speed is assumed to be 3600 rpm (So, when the reference speed is 0.5 pu, it is mean the speed equals 1800 rpm). The results proved that the drive system effectively works at an extensive range of speeds. In addition, the actual and estimated speeds have coincided. Moreover, from Figure 16, it is obviously seen that the current of the motor is sinusoidal.

Another case of study has been tested for more evaluating of the control scheme. In this case of study, the reference speed has been reversed from 0.4 pu to 0.2 pu in the reverse direction in a ramp variation. The results of this case of study are shown in Figures 17 and 18. Figure 17 shows the speed response of the control scheme. Moreover, the phase current is shown in Figure 18. The results show the control scheme has a good dynamic performance.

The last case of study has assumed many ramp changes in the references including reversing the speed. The rotor speed response is shown in Figure 19. The results have been plotted with the aid of CCS package and Digital Signal Processing (DSP). The results show the control scheme has a good dynamic performance.

**Figure 14.** The transient performance of the entire drive system under variable speed from 0.4 pu to 0.2 pu to 0.4 pu.

**Figure 15.** The transient performance of IqS of the entire drive system under variable speed from 0.4 pu to 0.2 pu.

**Figure 16.** Current of phase (**a**) at reference speeds of 0.2 pu to 0.4 pu.

**Figure 17.** The transient performance of IqS of the entire drive system under variable speed from 0.4 pu to 0.2 pu.

**Figure 18.** Current of phase (**a**) for the case of speed reversing from 0.4 pu to 0.2 pu.

**Figure 19.** The transient performance of multi-variation in the rotor speed with reversing (The experimental data and measurements have been collected with the aid of the DSP and plotted using Matlab plot tool).

#### **7. Conclusions**

In this paper, H∞ theory has been proposed for designing an optimal robust speed controller for a field-oriented induction motor drive. The design problem of the H∞ controller was explained and derived in standard form with an assertion on the choice of weighting functions, which fulfills the optimal robustness and performance of the drive system. The proposed control strategy has many advantages: it is robust to plant uncertainties, and has a simple implementation and a fast response. Moreover, a robust motor speed estimator based on the MRAS is presented that estimates motor speed accurately for a sensorless IFO control system. The validation of the induction motor drive was performed using both simulated and experimental implementations. The main conclusions that can be drawn from the results in this study are as follows:

(1) The effectiveness of the considered induction motor drive system with the proposed controller has been demonstrated.

(2) Compared with a PI classical controller, the response of the proposed controller shows a reduced settling time in the case of a sudden change of the speed command in addition to smaller values of the maximum speed dip and overshoot as a result of the application and removal of stepped changes in load torque.

(3) The proposed controller achieved robust performance under stepped speed change commands or changes in load torque even when the parameters of the controlled system were varied.

(4) The forward-reverse operation of the drive is obtained by the robust MRAS speed estimator and guarantees the stability of the proposed sensorless control to the system at a speed of zero. Moreover, the presented speed estimator provides an accurate speed estimation regardless of the load conditions.

(5) Both simulated and real-world experimental results demonstrate that the proposed control drive system is capable of working at a wide range of motor speeds and that it exhibits good performance in both dynamic and steady-state conditions.

Further research work should consider the nonlinearity of the induction machine parameters tacking saturation and/or iron losses into consideration. Additionally, recent optimization techniques may be applied to determine the optimal weight functions for designing the controller. Moreover, the operation range should be expanded to study and analyse the operation of the control scheme in the field weakening region. Moreover, the estimation of the machine parameters may be an interesting research point for future work for improving the overall performance of the control scheme and speed estimator.

**Author Contributions:** A.A.Z.D. and H.H.A. developed the idea and the simulation models. A.A.Z.D. performed the experiments and analyzed the data. A.A.Z.D., A.-H.M.E.-S. and H.H.A. wrote the paper. A.A.Z.D., A.-H.M.E.-S. and M.A.E.S. contributed by drafting and making critical revisions. All the authors organized and refined the manuscript to its present form.

**Funding:** This work was supported by Minia University, Egypt.

**Conflicts of Interest:** The authors declare no conflicts of interest.

#### **References**


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