  A model predictive control (MPC) scheme for a permanent-magnet synchronous
motor (PMSM) is presented. The torque controller optimizes a quadratic cost
consisting of control error and machine losses repeatedly, accounting the
voltage and current limitations. The scheme extensively relies on optimization,
to meet the runtime limitation, a suboptimal algorithm based on differential
flatness, continuous parameterization and linear programming is introduced.
  The multivariable controller exploits cross-coupling effects in the
long-range constrained predictive control strategy. The optimization results in
fast and smooth torque dynamics while inherently using field-weakening to
improve the power efficiency and the current dynamics in high speed operation.
As distinctive MPC feature, constraint handling is improved, instead of just
saturating the control input, field weakening is applied dynamically to bypass
the voltage limitation. The performance of the scheme is demonstrated by
experimental and numerical results.
