Distributed model predictive control of constrained spatially-invariant interconnected systems in input-output form
This paper proposes a non-iterative, Lyapunov-based distributed model predictive control (MPC) design for invariant spatially-interconnected systems comprised of a network of subsystems with coupled dynamcis and subject to local state and/or input constraints. Considered here is the distributed MPC design for linear systems in input-output form with fixed-structure local state-feedback-like control law. The proposed distributed MPC design approach ensures asymptotic stability and recursive feasibility, and its online implementation can be formulated as solving a linear matrix inequality (LMI) problem defined at the subsystem level. Simulation results using a heat equation in one-dimensional space demonstrate the merits and effectiveness of the proposed approach.