Robust Model Predictive Control Using Tubes
Abstract¶
A form of feedback model predictive control (MPC) that overcomes disadvantages of conventional MPC but which has manageable computational complexity is presented. The optimal control problem, solved on-line, yields a ‘tube’ and an associated piecewise affine control law that maintains the controlled trajectories in the tube despite uncertainty; computational complexity is linear (rather than exponential) in horizon length. Asymptotic stability of the controlled system is established.
Summary¶
Introduces a tube-based robust MPC formulation that computes a nominal tube and associated piecewise-affine feedback law to keep uncertain trajectories inside it. The approach reduces worst-case complexity growth with horizon length while preserving robust constraint satisfaction and asymptotic stability.