A two-level hierarchical model predictive control (MPC) formulation is presented for constrained linear systems operating over a mission. Mission-based MPC is applicable to many control applications where the system operates for a finite time and stability about an equilibrium is not the primary objective. Instead, the primary control objective is to guarantee constraint satisfaction during operation as well as terminal constraints imposed on the final state of the system at the end of the mission. The secondary control objective is reference tracking, where references determine the desired operation for the system. A hierarchical control formulation permits the upper level controller to plan state trajectories over the entire mission, while a lower level controller modifies these trajectories to improve reference tracking. This decomposition of the control problem reduces computational cost, enabling real-time implementation for large systems with long missions. Feasibility proofs guarantee the constraint satisfaction while a numerical example demonstrates the efficacy of the approach.
|Original language||English (US)|
|Title of host publication||2018 Annual American Control Conference, ACC 2018|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Aug 9 2018|
|Event||2018 Annual American Control Conference, ACC 2018 - Milwauke, United States|
Duration: Jun 27 2018 → Jun 29 2018
|Name||Proceedings of the American Control Conference|
|Other||2018 Annual American Control Conference, ACC 2018|
|Period||6/27/18 → 6/29/18|
Bibliographical noteFunding Information:
*Research supported by the National Science Foundation Engineering Research Center for Power Optimization of Electro Thermal Systems (POETS) with cooperative agreement EEC-1449548.
© 2018 AACC.