Nonlinear systems analysis (2nd ed.)
Nonlinear systems analysis (2nd ed.)
Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Worst-case formulations of model predictive control for systems with bounded parameters
Automatica (Journal of IFAC)
A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme with Guaranteed Stability
Automatica (Journal of IFAC)
Survey paper: Set invariance in control
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
A stabilizing model-based predictive control algorithm for nonlinear systems
Automatica (Journal of IFAC)
Enlargement of polytopic terminal region in NMPC by interpolation and partial invariance
Automatica (Journal of IFAC)
Constrained robust model predictive control based on periodic invariance
Automatica (Journal of IFAC)
Hi-index | 22.15 |
The use of time invariant linear state feedback control laws for the definition of terminal invariant regions can be conservative, thereby reducing the efficacy of predictive control in terms of size of stabilisable sets and closed-loop performance. This difficulty, which is particularly pronounced in the case of nonlinear and/or uncertain dynamics, can be remedied through the use of time-varying control laws and terminal invariant sets. In existing MPC schemes, however, these have to be computed online thereby rendering implementation impracticable for anything other than low-dimensional systems. Here, the definition of invariance is extended to apply over @n predicted control moves, thereby enabling the use of pre-determined (offline) time-varying state feedback gains. More importantly, this extension allows for the use of local uncertainty or linear difference inclusion sets, and thus affords significant improvements, e.g. in terms of the size of terminal regions.