Title:
複合動的システムの最適化制御を提供するための方法およびシステム
Document Type and Number:
Japanese Patent JP6564905
Kind Code:
B2
Abstract:
A method for performing an optimized control of a complex dynamical system (sys) using machine learned, scenario based control heuristics, the method comprising the steps of:
providing (S1) a simulation model (f) for predicting a system state vector (x) of said dynamical system (sys) in time based on a current scenario parameter vector (p) and a control vector (u); using (S2) a Model Predictive Control, MPC, algorithm to provide the control vector (u) at every time during a simulation of said dynamical system (sys) using said simulation model (f) for different scenario parameter vectors (p0, p1, p2, ..) and initial system state vectors (x00, x01, x02, ..); calculating (S3) for every simulated combination of a scenario parameter vector (p) and initial system state vector (x 0 ) a resulting optimal control value (u* (p, x 0 )) by the MPC algorithm and saving the resulting optimal control value; generating (S4) machine learned control heuristics (u a(p, x 0 )) approximating the relationship between the corresponding scenario parameter vector (p) and the initial system state vector (x 0 ) for the saved resulting optimal control value (u* (p, x 0 )) using a machine learning algorithm; and using the generated machine learned control heuristics to control (S5) the complex dynamical system (sys) modelled by said simulation model (f).
Inventors:
Dirk Hartmann
Birgit Opst
Eric Olof Johannes Wannaberg
Birgit Opst
Eric Olof Johannes Wannaberg
Application Number:
JP2018092884A
Publication Date:
August 21, 2019
Filing Date:
May 14, 2018
Export Citation:
Assignee:
Siemens Aktiengesellschaft
International Classes:
G06N20/00; G06N99/00
Domestic Patent References:
| JP2016100009A | ||||
| JP2016520464A |
Foreign References:
| US20160147203 | ||||
| WO2017006372A1 |
Attorney, Agent or Firm:
Iwao Yamaguchi
Hiroshi Yamamoto
Hiroshi Yamamoto