Abstract
Economic model predictive control (MPC) of induction motor drives minimizes a loss model that usually omits saturation, additional load loss, the core-loss increment under pulse-width modulation, and the junction-temperature dependence of switching energy. A published thermally adaptive economic MPC is extended in three ways. First, it is proven that the DC-link power residual is structurally blind to losses supplied through the air gap when torque is reconstructed from measured currents; therefore, only stator-terminal and converter losses can be learned without a torque sensor, and a physics-informed residual model is identified and fed to the thermal observer. Second, the magnetizing curve is learned from the reactive-power balance by a set-membership estimator contracted by monotonicity and concavity. Third, the guaranteed flux band tightens the current, torque-reserve, and voltage constraints of the economic target problem, whose feasible set grows monotonically during learning. In simulations of 2.2, 7.5, and 37 kW drives with pump and conveyor cycles and a structurally mismatched plant, the winding-temperature estimation error decreased from 5.5–10.7 K to 1.3–1.6 K, torque error from 0.74–1.45% to 0.24–0.40% of rated torque, cycle energy came within 0.06–0.23% of an oracle, and voltage-headroom violations were eliminated at an energy cost of 0.03–0.18 percentage points.