  A disturbance-aware predictive control policy is proposed for DC-AC power
inverters with the receding horizon optimization approach. First, a discrete
event-driven hybrid automaton model has been constructed for the nonlinear
inverter system dynamics. A control problem of infinite discrete state-space
transition sequence optimization is formulated. A receding horizon optimization
approach is applied to solve the discrete optimization problem piece-wisely
on-line. Accordingly, disturbance-aware adaptive control is proposed, the
external disturbance is sampled and estimated by an on-line Recursive Least
Square (RLS) algorithm. Then it is elaborated that the conventional PWM control
solution is a subset of solutions of the proposed control strategy and the
code-transition between them is provided. By adding extra PWM constraints to
the proposed control strategy, an Optimal PWM Control Mode (OPCM) is introduced
as an example. The proposed controller can freely operate under the original
Optimal Discrete Control Mode (ODCM) and the OPCM. The numerical simulation
results have verified that the proposed discrete control strategy has realized
disturbance-aware adaptive control of DC-AC inversion against load-shift, and
ODCM has better control performance than OPCM. In addition, the proposed
modeling and control frame has the potential to support other forms of control
modes.
