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Method to complete a learning cycle of a recursive least squares approximation

A technique of recursive least squares and learning cycles, applied in engine control, machine/engine, electrical control, etc.

Active Publication Date: 2013-07-31
GM GLOBAL TECH OPERATIONS LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

A system that behaves unpredictably over different operating ranges is said to be non-linear, meaning that observations made of the system's operation over one operating range may not be useful for predicting the system's operation over another

Method used

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  • Method to complete a learning cycle of a recursive least squares approximation
  • Method to complete a learning cycle of a recursive least squares approximation
  • Method to complete a learning cycle of a recursive least squares approximation

Examples

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Embodiment Construction

[0055] Referring to the accompanying drawings, which are shown for the purpose of describing certain exemplary embodiments only and not for the purpose of limiting them, a large number of analytical or statistical methods are known to The data points perform a curve fit or approximation to the behavior of a system exhibiting nonlinear behavior. One approach to learning properties of systems exhibiting nonlinear behavior involves approximation or determination using recursive least squares (RLS). Iterations of data collection and analysis can continue through learning cycles until the approximated system properties are sufficiently mapped such that a linear approximation curve can be used to control the system with high confidence.

[0056] Engines with direct fuel injection use fuel injectors to control precise fuel injection timing and fuel injection volume. Fuel injectors have non-linear behavior with different fuel injection characteristics at different fuel flow rates. T...

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Abstract

A method to control a non-linear system includes operating a learning cycle to approximate characteristics of the system and, once the learning cycle is complete, operating the system based upon the characteristics. The learning cycle includes monitoring operation of the system, approximating the characteristics of the system with a recursive least squares approximation based upon the monitored operation, comparing variance of the operation to a threshold variance, and completing the learning cycle based upon the variance exceeding the threshold variance.

Description

technical field [0001] The invention relates to approximating the properties of systems exhibiting non-linear behavior. Background technique [0002] The statements in this section merely provide background information related to the invention. Accordingly, such statements are not intended to constitute admissions of prior art. [0003] Modeling or approximating properties of a system is useful in methods of controlling the system. Systems that behave unpredictably over different operating ranges are said to be nonlinear, meaning that observations made of the system's operation over one operating range may not be useful for predicting the system's behavior over another operating range. [0004] Fuel injectors are used to inject fuel into the engine's combustion chambers. Fuel injectors provide pressurized fuel from a fuel rail to the combustion chambers. Fuel injectors are activated at one or more timings of the combustion cycle and remain open based on a controlled fuel...

Claims

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Application Information

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IPC IPC(8): F02D45/00
CPCF02D2200/0616F02D41/3035F02D41/04F02D41/2438F02D41/2467F02D45/00F02D2041/2058F02D41/2445F02D41/24
Inventor K-K.辛J-M.康H.允
Owner GM GLOBAL TECH OPERATIONS LLC
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