Hierarchical Model Predictive Speed and Current Control of an Induction Machine Drive With Moving-Horizon Load Torque Estimator

Speed-controlled induction machine (IM) drives are the working horses in many industrial applications. When applying model predictive control (MPC) to such tasks, two major challenges have to be faced: First, an accurate and dynamic load torque estimation is required for sufficient steady-state and transient control performance. Second, the speed and the underlying current control loop show widely differing time constants and, therefore, designing a control structure with sufficient prediction horizons for both control variables while ensuring real-time capability on typical hardware platforms is crucial. To overcome the latter problem, a hierarchical MPC approach with different sampling intervals for speed and current control is proposed. Furthermore, a moving-horizon estimator is seamlessly introduced within the speed MPC structure for suitable load torque computation. The proposed control framework is implemented on a rapid-control prototyping test bench utilizing the ACADO toolkit to solve the underlying optimization problems. The method's feasibility is demonstrated by experimental investigations on a laboratory test bench.