Constrained LQR Control of Dual Induction Motor Single Inverter Drive

Control of dual induction motor fed by a single voltage source inverter is a challenging task especially during unbalanced load conditions on each motor. Such drive configurations are common, for example, in traction. Conventional control algorithms solve the control of each motor in a separate control loop and the overall control action is designed as a weighted contribution of each control loop. In such a case, the control performance strongly relies on the specific design of weighting coefficients, which should be state dependent and time varying value in majority of cases. In this contribution, we formulate the control problem as an optimization task and investigate the use of state-dependent Riccati equation and predictive control concepts. We show that it is sufficient to consider a simple linear quadratic regulator (LQR) with rule-based predictive controller for current limitation. The proposed control algorithm naturally weights contribution of tracking error of each drive. Moreover, due to high level of symmetry in the system, only two parameters are tuned manually. Experimental testing is used to validate the control algorithm on a laboratory prototype of dual induction motor drive with a rated power of 2 x 4.5 kW.

Automated summary

The study proposes a control method for dual induction motors based on optimization tasks, incorporating state-dependent Riccati equations and predictive control concepts, using a simple linear quadratic regulator and rule-based predictive controller. The control algorithm, validated on a laboratory prototype, successfully controls the dual induction motors with manual adjustment of two parameters.