Method and apparatus for performing optimal control
AssigneesMakinaRocks Co., Ltd., Hanon Systems
InventorsSungho Joo, Jeonghoon Lee, Joongjae Kim, Je Yeol Lee, Dongmin Lee, Minseop Kim
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Abstract
According to an exemplary embodiment of the present disclosure, an optimal control method performed by a computing device including at least one processor is disclosed. The method includes acquiring state information including at least one state variable; calculating first control information by inputting the state information to a reinforcement learning control model; calculating second control information from the state information based on a feedback control algorithm; and calculating optimal control information based on the first control information and the second control information.
Claims17
An optimal control method performed by a computing device including at least one processor, the optimal control method comprising:
- acquiring state information, wherein the state information includes at least one state variable selected from subcool data, heater outlet temperature data, compressor output data, and valve open/close data, the at least one state variable being measured from a mobile heat-pump HVAC loop comprising a compressor, a valve, and a heater mounted in a vehicle;
- calculating first control information by inputting the state information to a reinforcement learning control model;
- calculating second control information from the state information based on a feedback control algorithm;
- calculating optimal control information based on the first control information and the second control information;
- and
- transmitting the optimal control information to one or more physical actuators to drive, in real time, at least one of the compressor, the valve, and the heater.
A computer program stored in a non-transitory computer readable storage medium, wherein when the computer program is executed by one or more processors, the computer program causes the one or more processors to perform the following operations to perform optimal control and the operations include:
- an operation of acquiring state information including at least one state variable from one or more sensors mounted on a vehicle energy system;
- an operation of calculating first control information by inputting the state information to a reinforcement learning control model;
- an operation of calculating second control information from the state information based on a feedback control algorithm;
- an operation of calculating optimal control information by performing a weighted sum of the first control information and the second control information, wherein a confidence score is calculated by the reinforcement learning control model, and a weight for the first control information is set to increase as the confidence score increases, and a weight for the second control information is set to decrease as the confidence score increases, such that as the confidence score increases, a contribution of the first control information relative to the second control information in the weighted sum increases;
- and
- an operation of transmitting the optimal control information to one or more physical actuators to drive, in real time, at least one of a compressor, a valve, and a heater of the vehicle energy system.
An apparatus for performing optimal control, comprising:
- one or more processors;
- a memory;
- and
- a network unit, wherein the one or more processors are configured to:
- acquire state information including at least one state variable from one or more sensors mounted on a vehicle energy system, the state information comprising real-time measurement values related to the operation of the vehicle energy system;
- calculate first control information by inputting the state information to a trained reinforcement learning control model implemented as a neural network executed by the processor;
- calculate second control information from the state information based on a feedback control algorithm executed by the processor, the feedback control algorithm comprising at least one of a proportional (P), proportional-integral (PI), and proportional-integral-differential (PID) control algorithm;
- calculate an error between the first control information and the second control information;
- compare the error to a previously determined error threshold;
- select, as optimal control information, one of the first control information or the second control information according to whether the error exceeds the error threshold, such that if the error is less than or equal to the error threshold, the first control information is selected as the optimal control information, and if the error is greater than the error threshold, the second control information is selected as the optimal control information;
- and
- transmit the optimal control information to one or more physical actuators to drive, in real time, at least one of a compressor, a valve, and a heater of the vehicle energy system, thereby manipulating the physical state of the vehicle energy system.
Dependencies are inferred from the claim text.