Learning-model predictive control with multi-step prediction for vehicle motion control
US12296839B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Nov 30, 2022 |
| Grant date | May 13, 2025 |
| Priority date | — |
| Expiry date | Aug 18, 2043 |
Classification
- Technology area (CPC B)Performing Operations; Transporting
- CPC primaryB60W2556/50
- WIPO fieldTransport
- WIPO sectorMechanical engineering
Abstract
A system for learning-model predictive control (LMPC) with multi-step prediction for motion control of a vehicle includes sensors and actuators. One or more control modules each having a processor, a memory, and input/output (I/O) ports are in communication with the sensors and actuators, the processor executing program code portions stored in the memory. The program code portions cause the sensors and actuators to obtain vehicle state information, receive a driver input, and generate a desired dynamic output based on the driver input and the vehicle state information. A program code portion estimates actions of the actuators based on the vehicle state information and the driver input, and utilizes the vehicle state information, the driver input, and the estimated actions of the actuators to select one or more models of a physics-based vehicle model and a machine-learning model of the vehicle to selectively adjust commands to the actuators.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.