  This paper proposes a stabilising model predictive control (MPC) scheme with
preview information of disturbance for nonlinear systems. The proposed MPC
algorithm is able to not only reject disturbance by making use of disturbance
preview information as necessary, but also take advantage of the disturbance if
it is good for a control task. This is realised by taking into account both the
task (e.g. reference trajectory) and disturbance preview in the prediction
horizon when performing online optimisation. Conditions are established to
ensure recursive feasibility and stability under the disturbance. First the
disturbance within the horizon is augmented with the state to form a new
composite system and then the stage cost function is modified accordingly. With
the help of input-to-state stability theory, a terminal cost and a terminal
constraint are constructed and added to the MPC algorithm with preview to
guarantee its recursive feasibility and stability under a pre-bounded
disturbance. Numerical simulation results demonstrate the effectiveness of the
proposed MPC algorithm.
