The invention discloses a crisscross optimization robust
model predictive control method for an automatic sweeping
robot. The crisscross optimization robust
model predictive control method is adaptive to a trajectory
tracking system with parameter uncertainty. According to the method, a discrete time controlled
system with parameter uncertainty, a reference trajectory
system and a
tracking error system are constructed, performance evaluation indexes are defined, the stable control
gain range of a basic RMPC controller is determined by solving a minimum and maximum
optimization problem and
linear matrix inequality constraints, and a multi-objective optimization function is combined in the range to achieve the stable control of the RMPC controller. The optimal additional control
gain is iteratively searched by means of a crisscross
algorithm, an optimized controller is formed, the stability and the dynamic performance are considered, the influence caused by parameter uncertainty can be overcome, the rising time and the adjusting time of trajectory tracking are remarkably shortened, the
tracking error and the
energy consumption are reduced, and the tracking efficiency is improved. And the dual requirements of the automatic sweeping
robot on real-
time response and control precision are met.