Intelligent controller providing time to target state

• US 8,452,457 B2
• Filed: 09/30/2012
• Issued: 05/28/2013
• Est. Priority Date: 10/21/2011
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Nest Labs Incorporated (Alphabet Inc.)
• Inventors: Matsuoka, Yoky, Sharan, Rangoli, Stefanski, Mark D., Ruff, Joseph Adam
• Primary Examiner(s): KASENGE, CHARLES R
• Application Number:
  US13/632,028
• Publication Number:
  US 20130103621A1
• Time in Patent Office: 240 Days
• Field of Search: 700/28, 700/29, 700/30, 700/275, 700/276, 700/278, 700/299, 700/300, 236/46.R, 236/91.C, 236/91.D, 236/91.E, 236/91.F
• US Class Current: 700/276
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/52 Indication arrangements, e.g. displays
• CPC Class Codes: F24F 11/58 using Internet communication
• CPC Class Codes: F24F 11/61 using timers
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/63 Electronic processing
• CPC Class Codes: F24F 11/64 using pre-stored data
• CPC Class Codes: G05B 13/04 involving the use of models or simulators
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05D 23/19 characterised by the use of electric means G05D23/1393 takes precedence
• CPC Class Codes: G05D 23/1902 characterised by the use of a variable reference value
• CPC Class Codes: H04L 12/2816 Controlling appliance services of a home automation network by calling their functionalities arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station; in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom H04Q9/00
• CPC Class Codes: H04L 12/2825 Reporting to a device located outside the home and the home network access arrangements H04L12/2856; for remote control or remote monitoring of applications H04L67/025; telephonic communication systems adapted for combination with telemetering systems H04M11/002
• CPC Class Codes: H04L 12/40013 Details regarding a bus controller
• CPC Class Codes: H04L 2012/285 Generic home appliances, e.g. refrigerators

Abstract

The current application is directed to intelligent controllers that continuously, periodically, or intermittently calculate and display the time remaining until a control task is projected to be completed by the intelligent controller. In general, the intelligent controller employs multiple different models for the time behavior of one or more parameters or characteristics within a region or volume affected by one or more devices, systems, or other entities controlled by the intelligent controller. The intelligent controller collects data, over time, from which the models are constructed and uses the models to predict the time remaining until one or more characteristics or parameters of the region or volume reaches one or more specified values as a result of intelligent controller control of one or more devices, systems, or other entities.

Claims

1. An intelligent controller that controls an environment, the intelligent controller comprising:

a processor;

a memory that stores a control schedule;

a current control schedule stored in the memory;

one or more sensors that sense current values of an environmental parameter;

instructions stored within the memory that, when executed by the processor, control the intelligent controller, during a response time following an immediate-control input or a scheduled setpoint change recorded in the control schedule, to

at each of multiple points in time,

record, in the memory, a current value for the environmental parameter,

when the environmental parameter values recorded in memory fit a local model for change in the parameter with time,

determine a remaining response time using the local model, storing the determined response time in memory, and displaying the remaining response time on a display device, and

when the environmental parameter values do not fit a local model but fit a global model,

determine a remaining response time using the global model, storing the determined response time in memory, and displaying the remaining response time on the display device.

2. The intelligent controller of claim 1 wherein the processor includes one or more of:

one or more local processors; and

one or more remote processors.

3. The intelligent controller of claim 1 wherein the memory includes one or more of:

one or more local electronic memories;

one or more local mass-storage devices;

one or more remote electronic memories; and

one or more remote mass-storage devices.

4. The intelligent controller of claim 1 wherein the current control schedule stored in the memory includes one or more setpoints, each setpoint associated with a time and one or more parameter values.

5. The intelligent controller of claim 1 wherein the display device is one of

a local display device included within the intelligent controller or directly connected to the intelligent controller via a wire, cable, optical fiber, or other transmission medium;

and

a remote display device to which the remaining response time is transmitted by the intelligent controller through a remote-display interface.

6. The intelligent controller of claim 1 wherein the environmental parameter values recorded in memory fit a local model for change in the parameter with time when a fitness metric computed for the environmental parameter values recorded in memory with respect to the local model is within a range of fitness values.

7. The intelligent controller of claim 6 wherein the fitness metric is a sum of terms, each term a squared difference between an observed parameter value and a parameter value calculated from the local model divided by the parameter value calculated from the local model.

8. The intelligent controller of claim 6 wherein the fitness metric is a probability computed from a probability distribution function.

9. The intelligent controller of claim 1 wherein determining a remaining response time using the local model further includes computing the remaining response time from a local-model function, parameterized by one or more parameters, that receives a current time as an argument.

10. The intelligent controller of claim 1 wherein the local model is a linear function parameterized by a constant slope parameter.

11. The intelligent controller of claim 1 wherein determining a remaining response time using the global model further includes computing the remaining response time from a global-model function, parameterized by one or more parameters, that receives a current time as an argument.

12. The intelligent controller of claim 1 wherein the global model is selected from among multiple parameterized functions by selecting a parameterized function and a constant value for each of one or more function parameters that statistically fits environmental parameter values stored in a plot in memory.

13. The intelligent controller of claim 12 wherein the environmental parameter values stored in the plot in memory are recorded over one or more response times, transferred from the memory to the plot after each of the one or more response times.

14. The intelligent controller of claim 12 wherein the intelligent controller maintains multiple global models, a global model selected from the multiple global model for use in computing a remaining response time that is associated with conditions closest to current conditions.

15. The intelligent controller of claim 12 wherein the intelligent controller maintains multiple local models, a local model selected from the multiple local model for use in computing a remaining response time that best fits the environmental parameter values recorded in memory.

16. A method incorporated in the control logic of an intelligent thermostat that includes a processor, a memory that stores a control schedule, a current control schedule stored in the memory, and one or more sensors that sense current values of an environmental parameter, the method comprising:

at each of multiple points in time,

recording, in the memory, a current value for the environmental parameter,

when the environmental parameter values recorded in memory fit a local model for change in the parameter with time,

determining a remaining response time using the local model, storing the determined response time in memory, and displaying the remaining response time on a display device, and

when the environmental parameter values do not fit a local model but fit a global model,

determining a remaining response time using the global model, storing the determined response time in memory, and displaying the remaining response time on the display device.

17. The method of claim 16 wherein determining a remaining response time using the global model further includes computing the remaining response time from a global-model function, parameterized by one or more parameters, that receives a current time as an argument.

18. The method of claim 17 wherein the global model is selected from among multiple parameterized functions by selecting a parameterized function and a constant value for each of one or more function parameters that statistically fits environmental parameter values stored in a plot in memory, the environmental parameter values stored in the plot in memory recorded over one or more response times, transferred from the memory to the plot after each of the one or more response times.

19. The method of claim 16 wherein the environmental parameter values recorded in memory fit a local model for change in the parameter with time when a fitness metric computed for the environmental parameter values recorded in memory with respect to the local model is within a range of fitness values.

20. The method of claim 16 wherein the fitness metric is a sum of terms, each term a squared difference between an observed parameter value and a parameter value calculated from the local model divided by the parameter value calculated from the local model.