# New Stable Non-Vector Control Structure for Induction Motor Drive
## 7 Experimental Verification of the IM Drive Speed Control on a Laboratory Model  
The linear model reference control structure is verified on the three-phase induction motor TYPE 1 AV3104B (400 V, 2.2 kW, 1465 RPM, 14.3 Nm) driven by the VQFREM 400 004-4 MA power converter (400 V, 11 A), manufactured by VONSCH Co, Brezno, Slovakia. The structure of the experimental setup is shown in Figure 14.  
The control board of the power converter has two processors DSP TMS230F2406. The first DSP processes signals from the current, DC-link, and position sensors. It also performs the Clarke and Park transformations and uses PI type controllers with a sample time of 50 us controls the stator currents \(i_{1x}\) and \(i_{1y}\) in the \(\{x,y\}\) reference frame. The second DSP implements the speed control and communicates with a higher-level controller and operator console. The speed control sample time is 1 ms. The fast current control loop is written in assembler language and the rest of the code is written in C. The Texas Instruments software development toolchain is used for programming DSPs. The setup with the input choke, power converter, and brake resistors is shown in Figure 15.  
To verify experimentally the proposed control structure in Figure 4, several measurements were performed on a laboratory model with IM at its starting to the rated speed \(\omega_{m}=150\) rad/s in time \(t=0.5\) s. An influence of the optional positive parameter in the reference model \(\alpha\) on the motor dynamics was investigated. For example, Figure 16a shows the control dynamics for the parameter \(\alpha=5\) (Equation (23)) and the values of the optional vector \(\mathbf{k}^{T}\) elements \(\mathbf{k}^{T}=[0.0031  
Figure 14: The structure of the experimental setup with VQFREM 400 004–4 MA power converter. Figure 13: Comparison of proposed control structure and vector control for moment of inertia changed to \(J=0.5\,J_{N}\) and \(J=2\,J_{N}\). In the graphs, the time courses of the model state variables \(x_{1M}\), \(x_{2M}\), prescribing the required dynamics for the motor angular speed and acceleration are compared with their measured values. The time courses of the measured quantities show a very good agreement with the reference model. Figure 16b shows time similar courses when decreasing the optional gain of the elements of the vector \(\mathbf{k}^{T}\) to 25% of their original value. It is obvious that the introduced change influences the time course of variables in dynamic states (e.g., here the state variable \(x_{2}\) oscillates less, but it has a larger absolute deviation from the reference model). It is important that again a substantial agreement between the measured quantities and the reference model outputs has been reached. The time courses in Figure 17a show the dynamics of the IM drive starting at 300% change of the controller optional gain \(\mathbf{k}^{T}\) against its original value. Due to the substantial increase of the gain in the control circuit, the state variable \(x_{2}\) (presenting the acceleration proportional to the motor dynamic torque) is visibly more oscillating, while the output variable \(x_{1}\) (IM speed) practically follows the reference model. The starting of the motor from the non-energized state and its stopping for the values of the control parameters valid for Figure 16a are shown in Figure 17b (here the simulation was performed for the motor starting in time \(t=0\)). One can observe here that the motor follows the reference model both during starting and stopping, i.e., it behaves as a linear system according to the reference model (23). Therefore, the proposed control structure is able to ensure the quality of the angular speed IM control within the whole control range. The experimental measurements confirm that the controlled drive behaves with high accuracy as its reference model, where for this case an optimal 2 nd order linear system was chosen. The reference model dynamics are determined by the optional parameter \(\alpha\) and the gain vector \(\mathbf{k}^{T}\).