Switched reluctance motor

Current (fluid)

Operating system

Magnet

Voltage

Rotor (electric)

Compensation (psychology)

Computer science

Process (computing)

Model predictive control

Magnetic reluctance

Engineering

Mechanical engineering

Thermodynamics

Control (management)

Synchronous motor

Artificial intelligence

Control theory (sociology)

Psychoanalysis

Psychology

Electrical engineering

Physics

Control engineering

Torque

IEEE Transactions on Industry Applications

The performances of a model predictive control algorithm largely depend on the knowledge of the system model. A model-free predictive control approach skips all the effects of parameters variations or mismatches, as well as of model nonlinearity and uncertainties. A finite-set model-free current predictive control is proposed in this paper. The current variations predictions induced by the eight base inverter voltage vectors are estimated by means of the previous measurements stored into lookup tables. To keep the current variations information up to date, the three current measurements due to the three most recent feeding voltages are combined together to reconstruct all the others. The reconstruction is performed by taking advantage of the relationships between the three different base voltage vectors involved in the process. In particular, 210 possible combinations of three-state voltage vectors can be found, but they can be gathered together in six different groups. A light and computationally fast algori...

An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives