Name
Abstract | ||
|---|---|---|
We consider the Chance Constrained Model Predictive Control problem for polynomial systems subject to disturbances. In this problem, we aim at finding optimal control input for given disturbed dynamical system to minimize a given cost function subject to probabilistic constraints, over a finite horizon. The control laws provided have a predefined (low) risk of not reaching the desired target set. Building on the theory of measures and moments, a sequence of finite semidefinite programmings are provided, whose solution is shown to converge to the optimal solution of the original problem. Numerical examples are presented to illustrate the computational performance of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CDC.2016.7799223 | 2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC) |
Field | DocType | ISSN |
Mathematical optimization,Optimal control,Polynomial,Model predictive control,Regular polygon,Probabilistic logic,Finite horizon,Dynamical system,Mathematics | Conference | 0743-1546 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jasour, A.M.Z. | 1 | 11 | 3.51 |
| Constantino M. Lagoa | 2 | 164 | 25.38 |