ONLINE SYSTEM IDENTIFICATION FOR CONTROLLING A MACHINE

• US 20170089043A1
• Filed: 09/25/2015
• Published: 03/30/2017
• Est. Priority Date: 09/25/2015
• Status: Abandoned Application

• Current Assignee: Caterpillar Incorporated
• Original Assignee: Caterpillar Incorporated
• Inventors: CHASE, James Sheridan, CHANG, Insu, JALIWALA, Salim Aziz
• Application Number:
  US14/865,864
• Publication Number:
  US 20170089043A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: E02F 3/435 for dipper-arms, backhoes or the like
• CPC Class Codes: E02F 9/2025 Particular purposes of control systems not otherwise provided for E02F3/16, E02F3/26, sub-groups of E02F3/43, E02F3/651, sub-groups of E02F3/84, E02F3/907, E02F5/145 take precedence
• CPC Class Codes: E02F 9/264 Sensors and their calibration for indicating the position of the work tool
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 19/042 using digital processors G05B19/05 takes precedence
• CPC Class Codes: G05B 2219/23005 Expert design system, uses modeling, simulation, to control design process

Abstract

A control system for a machine may include an electronic controller configured to receive a sensor signal indicative of an operational parameter of the machine, and to output a control signal to an actuator to control an operational characteristic of the machine. The electronic controller may include a poles-zeros identification module, an onboard system identification module configured for online, real-time identification of one or more transfer functions that govern a dynamic relationship between one or more inputs and one or more outputs of at least one plant model, wherein the at least one plant model is representative of behaviors of the machine and simulates a dynamic influence of the operational parameter, and a comparator that determines the accuracy of a plant model.

Claims

1. A control system for a machine, comprising:

one or more sensors and actuators configured to measure and control operational characteristics of the machine; and

an electronic controller mounted onboard the machine, the electronic controller being configured to receive a sensor signal indicative of an operational parameter of the machine, and to output a control signal to an actuator to control an operational characteristic of the machine, the electronic controller including;

a poles-zeros identification module configured for determining poles of one or more transfer functions as roots of the denominator of the one or more transfer functions and determining zeros of the one or more transfer functions as roots of the numerator of the one or more transfer functions;

an onboard system identification module configured for online, real-time identification of the one or more transfer functions that govern a dynamic relationship between one or more inputs and one or more outputs of at least one plant model, wherein the at least one plant model is representative of behaviors of the machine and simulates a dynamic influence of the operational parameter on a desired output of the machine, the onboard system identification module being further configured to define an order of a numerator of the one or more transfer functions and an order of a denominator of the one or more transfer functions based on a complexity of the dynamic relationship between the one or more inputs and the one or more outputs;

a testing module configured for generating a reference signal and supplying the reference signal as an input to the one or more transfer functions; and

a comparator configured for determining an accuracy of the at least one plant model by determining an error between a measured response of the machine to the reference signal and a predicted response obtained from the one or more transfer functions with the poles and zeros.

2. The control system of claim 1, further including:

a user interface configured to present to a machine operator in real-time at least one plant model identified by the onboard system identification module and an associated accuracy of the at least one plant model as determined by the comparator, and the user interface further configured to receive a selection by the machine operator of at least one of a preferred plant model or a request for identification of a plant model with an improved accuracy.

3. The control system of claim 1, wherein the one or more sensors and actuators are configured to provide input and output variables corresponding to at least one of position and movement of a work implement of the machine.

4. The control system of claim 1, wherein the electronic controller is further configured to:

determine locations of the poles and zeros for each of a plurality of transfer functions using the poles-zeros identification module; and

iteratively identify the plurality of transfer functions governing the dynamic relationships between multiple inputs and multiple outputs of a succession of plants.

5. The control system of claim 4, wherein the electronic controller is further configured to:

determine an error for each of the plurality of transfer functions using the comparator;

select a transfer function of the plurality of transfer functions that results in an error that is less than an error of a previous iteration of a transfer function; and

continue to identify iterations of transfer functions until a selected transfer function no longer results in an error that is less than an error of a previous iteration of a transfer function.

6. The control system of claim 4, wherein the electronic controller is further configured to:

determine a rise time for the control system that is a function of the time needed by the control system to reach a desired output value after a change in an input to the control system; and

determine a DC gain for the control system.

7. The control system of claim 4, wherein the electronic controller is further configured to:

determine whether an identified transfer function is representative of a stable system by determining whether the number of zeros for the identified transfer function is less than or equal to the number of poles; and

define ranges for locations of zeros and poles, a DC gain, and a maximum number of iterations to be performed in selecting the locations of poles and zeros for each number of poles and zeros that generate a transfer function with an error that is less than an error of any previous iteration of a transfer function.

8. The control system of claim 7, wherein the electronic controller is further configured to select a transfer function with an error that is less than an error of any previous iteration of a transfer function by performing an optimization technique to determine locations of the poles and zeros of one of the plurality of identified transfer functions that result in the smallest error of all of the identified transfer functions.

9. The control system of claim 8, wherein the electronic controller is further configured to:

define a maximum number of iterations for identifying a subset of the plurality of transfer functions, with each of the transfer functions in the subset having a number of poles within a predefined range and a number of zeros within a predefined range;

generate a pseudo-random-binary-sequence (PRBS) signal;

supply the PRBS signal to each of the transfer functions in the subset of the plurality of transfer functions;

determine a predicted response of the machine to the PRBS signal using locations of the poles and the zeros for each transfer function;

calculate an error for each transfer function by subtracting the predicted response from an actual response of the machine to the PRBS signal; and

identify a transfer function in the subset with the smallest error based on the locations of the poles and the zeros for the transfer function.

10. A method of controlling a machine, the method comprising:

measuring an operational parameter characterizing operation of the machine using a sensor;

receiving at an onboard electronic controller a sensor signal from the sensor indicative of the operational parameter of the machine;

outputting a control signal from the onboard electronic controller to an actuator to control an operational characteristic of the machine;

determining poles of one or more transfer functions as roots of the denominator of the one or more transfer functions and determining zeros of the one or more transfer functions as roots of the numerator of the one or more transfer functions;

identifying in real-time the one or more transfer functions using a system identification module that is included in the onboard electronic controller, wherein the one or more transfer functions govern a dynamic relationship between one or more inputs and one or more outputs of at least one plant, and wherein the at least one plant model is representative of behaviors of the machine and simulates a dynamic influence of the operational parameter on a desired output of the machine;

defining an order of the one or more transfer functions based on a complexity of the dynamic relationship between the one or more inputs and the one or more outputs;

generating a reference signal and supplying the reference signal as an input to the one or more transfer functions; and

determining an accuracy of the at least one plant model by determining an error between a measured response of the machine to the reference signal and a predicted response calculated from locations of the poles and zeros of the one or more transfer functions.

11. The method of claim 10, further including:

presenting to a machine operator in real time on a user interface the at least one plant model and an associated accuracy of the at least one plant model; and

receiving on the user interface a selection by the machine operator of at least one of a preferred plant model or a request for identification of a plant model with an improved accuracy.

12. The method of claim 10, further including providing inputs and outputs of the at least one plant model corresponding to at least one of a position and movement of a work implement of the machine.

13. The method of claim 10, further including:

determining locations of the poles and zeros for each of a plurality of transfer functions; and

iteratively identifying the plurality of transfer functions governing the dynamic relationships between multiple inputs and multiple outputs of a succession of plant models.

14. The method of claim 13, further including:

determining an error for each of the plurality of transfer functions;

selecting a transfer function of the plurality of transfer functions that results in an error that is less than an error of a previous iteration of a transfer function; and

continuing to identify iterations of transfer functions until a selected transfer function no longer results in an error that is less than an error of a previous iteration of a transfer function.

15. The method of claim 13, further including:

determining a rise time for the control system that is a function of the time needed by the control system to reach a desired output value after a change in an input to the control system; and

determining a DC gain for the control system.

16. The method of claim 13, further including:

determining whether an identified transfer function is representative of a stable system by determining whether the number of zeros for the identified transfer function is less than or equal to the number of poles; and

defining ranges for locations of zeros and poles, a DC gain, and a maximum number of iterations to be performed in selecting the locations of poles and zeros for each number of poles and zeros that generate a transfer function with an error that is less than an error of any previous iteration of a transfer function.

17. The method of claim 16, further including selecting a transfer function with an error that is less than an error of any previous iteration of a transfer function by performing a Monte Carlo simulation to determine locations of the poles and zeros of one of the plurality of identified transfer functions that result in the smallest error of all of the identified transfer functions.

18. The method of claim 17, further including:

defining a maximum number of iterations for identifying a subset of the plurality of transfer functions, with each of the transfer functions in the subset having a number of poles within a predefined range and a number of zeros within a predefined range;

generating a pseudo-random-binary-sequence (PRBS) signal;

supplying the PRBS signal to each of the transfer functions in the subset of the plurality of transfer functions;

determining a predicted response of the machine to the PRBS signal using locations of the poles and the zeros for each transfer function;

calculating an error for each transfer function by subtracting the predicted response from an actual response of the machine to the PRBS signal; and

identifying a transfer function in the subset with the smallest error based on the locations of the poles and the zeros for the transfer function.

19. A computer-readable medium for use in a machine control system, the computer-readable medium comprising computer-executable instructions for performing a method with at least one processor of an onboard electronic controller of a machine, wherein the method comprises:

receiving at the onboard electronic controller a sensor signal from a sensor indicative of an operational parameter of the machine;

outputting a control signal from the onboard electronic controller to an actuator to control an operational characteristic of the machine;

determining poles of one or more transfer functions as roots of the denominator of the factored form of the one or more transfer functions and zeros of the one or more transfer functions as roots of the numerator of the factored form of the one or more transfer functions;

identifying in real-time the one or more transfer functions using a system identification module that is included in the onboard electronic controller, wherein the one or more transfer functions govern a dynamic relationship between one or more inputs and one or more outputs of at least one plant model, and wherein the at least one plant model is representative of behaviors of the machine and simulates a dynamic influence of the operational parameter on a desired output of the machine;

defining an order of the one or more transfer functions based on a complexity of the dynamic relationship between the one or more inputs and the one or more outputs;

generating a reference signal and supplying the reference signal as an input to the one or more transfer functions; and

determining an accuracy of the at least one plant model by determining an error between a measured response of the machine to the reference signal and a predicted response calculated from locations of the poles and zeros of the one or more transfer functions.

20. The computer-readable medium of claim 19, wherein the method further includes:

determining locations of poles and zeros for each of a plurality of transfer functions;

iteratively identifying a plurality of transfer functions governing the dynamic relationships between multiple inputs and multiple outputs of a succession of plant models;

determining an error for each of the plurality of transfer functions;

selecting a transfer function of the plurality of transfer functions that results in an error that is less than an error of a previous iteration of a transfer function; and

continuing to identify iterations of transfer functions until a selected transfer function no longer results in an error that is less than an error of a previous iteration of a transfer function.