Patent ID: 11868887
Assignee: ROBERT BOSCH GMBH
Field: Control (Instruments)
Classification: CPC G | IPC G

Claim 14:
15. A system implementing a trained model that uses a stochastic differential equation (SDE) that includes a set of SDE variables having a drift component and a diffusion component, wherein the drift component includes a predefined part whose parameters are fixed and a trainable part whose parameters have been adjusted by a training that optimizes a contribution of the trainable part of the drift component to an overall drift, the system comprising:
a computer-controlled subsystem; and
a processor subsystem, wherein, during operation of the computer-controlled subsystem, the processor subsystem is configured to:
use at least one sensor to continually obtain a measurement of at least one physical quantity of the computer-controlled subsystem and/or an environment of the computer-controlled subsystem;
use the model to make a time-series prediction of a state of the computer-controlled subsystem at a current time point based on values of the set of variables of the SDE that represent the measurements of the physical quantities at a previous time point wherein the making of the prediction includes:
evaluating the predefined part of the drift component to obtain a first drift;
evaluating the trainable part of the drift component to obtain a second drift;
combining the first drift with a and the second drift to obtain an overall drift; and
identifying, as the predicted state, a state corresponding to the overall drift with a stochasticity characterized by the diffusion component; and

based on the prediction, modify an operational parameter of the computer-controlled subsystem controlling at least one actuator of the computer-controlled subsystem.