# US 2014/0156085 A1 · Radiant heating controls and methods for an environmental control system > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0156085 A1 - Document ID: US20140156085A1 - Status: Published application - Kind: A1 - Application number: 14/085,594 - Filed: 2013-11-20 - Published: 2014-06-05 - Earliest claimed: 2012-09-30 - Assignees: Nest Labs, Inc. - Applicants: Nest Labs, Inc. - Inventors: Yash Modi; Yoky Matsuoka; Mark Malhotra - Web page: https://patentgrep.com/patent/US20140156085A1 ## CPC - F24F 11/46: Improving electric energy efficiency or saving - F24F 11/30: for purposes related to the operation of the system, e.g. for safety or monitoring - F24F 11/523: for displaying temperature data - F24F 11/58: using Internet communication - F24F 11/62: characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values - F24F 11/64: using pre-stored data - F24F 11/65: for selecting an operating mode - F24F 11/88: Electrical aspects, e.g. circuits - G05B 13/04: involving the use of models or simulators - G05D 23/19: characterised by the use of electric means {(G05D23/1393 takes precedence)} - G05D 23/1919: {characterised by the type of controller} - G06N 5/048: Fuzzy inferencing - F24F 2110/10: Temperature - F24F: AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING (removing dirt or fumes from areas where they are produced B08B15/00; vertical ducts for carrying away waste gases from buildings E04F17/02; tops for chimneys or ventilating shafts, terminals for flues F23L17/02) - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Embodiments of the invention describe thermostats that use model predictive controls and related methods. A method of controlling a thermostat using a model predictive control may involve determining a parameterized model. The parameterized model may be used to predicted ambient temperature values for an enclosure. A set of radiant heating system control strategies may be selected for evaluation to determine an optimal control strategy from the set of control strategies. To determine the optimal control strategy, a predictive algorithm may be executed, in which each control strategy is applied to the parameterized model to predict an ambient temperature trajectory and each ambient temperature trajectory is processed in view of a predetermined assessment function. Processing the ambient temperature trajectory in this manner may involve minimizing a cost value associated with the ambient temperature trajectory. The radiant heating system may subsequently be controlled according to the selected optimal control strategy. ## Claims ### Claim 1 A thermostat comprising: a housing; a memory; and a processing system disposed within the housing and being in operative communication with the memory and with a radiant heating system, the processing system being configured and programmed to control the radiant heating system according to the steps of: determining a parameterized model from which a temperature response of an enclosure responsive to a candidate radiant heating control strategy may be determined, the parameterized model being based at least in part on historical temperature information stored in said memory and acquired during at least one historical period in which the enclosure was heated by the radiant heating system under the control of said thermostat; determining an optimal radiant heating control strategy from among a plurality of candidate radiant heating control strategies by using said parameterized model to compute a plurality of predicted temperature responses corresponding respectively to the plurality of candidate radiant heating control strategies and processing said predicted temperature responses according to one or more predetermined assessment criteria; and controlling the radiant heating system according to the determined optimal radiant heating control strategy. ### Claim 2 (depends on 1) The thermostat of claim 1, wherein the memory is disposed within the housing, and wherein one or more temperature sensors are also disposed within the housing. ### Claim 3 (depends on 2) The thermostat of claim 2, wherein the processing system includes a first relatively high-powered processor that is configured and programmed to determine the parameterized model and to determine the optimal radiant heating control strategy by computing the plurality of predicted temperature responses, and wherein the processing system includes a second relatively low-powered processor that is in operative communication with the one or more temperature sensors to determine an ambient temperature. ### Claim 4 (depends on 3) The thermostat of claim 3, wherein the thermostat includes a rechargeable battery and the first processor is configured to transition between a wake state and a sleep state, wherein each time the first processor transitions from the sleep state to the wake state, the parameterized model and/or optimal radiant heat control strategy is re-determined based at least in part on ambient temperature readings determined by the second processor during the sleep state of the first processor. ### Claim 5 (depends on 1) The thermostat of claim 1, wherein each candidate radiant heating control strategy is binary-valued. ### Claim 6 (depends on 1) The thermostat of claim 1, wherein a first optimal radiant heat strategy covering a first time period is determined and executed to control the radiant heating system during the first time period, and wherein a second optimal radiant heat control strategy is determined during the first time period and executed prior to an end of the first time period to control the radiant heating system. ### Claim 7 (depends on 1) The thermostat of claim 1, wherein the processing system is further configured and programmed to determine a Lag value that represents at least in part an amount of system inertia for the enclosure. ### Claim 8 A method of controlling a thermostat comprising: providing a thermostat comprising: a housing; a memory; and a processing system disposed within the housing and being in operative communication with the memory and with a radiant heating system, the processing system being configured and programmed to control the radiant heating system; determining a parameterized model from which a temperature response of an enclosure responsive to a candidate radiant heating control strategy may be determined, the parameterized model being based at least in part on historical temperature information stored in said memory and acquired during at least one historical period in which the enclosure was heated by the radiant heating system under the control of said thermostat; determining an optimal radiant heating control strategy from among a plurality of candidate radiant heating control strategies by using said parameterized model to compute a plurality of predicted temperature responses corresponding respectively to the plurality of candidate radiant heating control strategies and processing said predicted temperature responses according to one or more predetermined assessment criteria; and controlling the radiant heating system according to the determined optimal radiant heating control strategy. ### Claim 9 (depends on 8) The method of claim 8, wherein the memory is disposed within the housing, and wherein one or more temperature sensors are also disposed within the housing. ### Claim 10 (depends on 9) The method of claim 9, wherein the processing system includes a first relatively high-powered processor that is configured and programmed to determine the parameterized model and to determine the optimal radiant heating control strategy by computing the plurality of predicted temperature responses, and wherein the processing system includes a second relatively low-powered processor that is in operative communication with the one or more temperature sensors to determine an ambient temperature. ### Claim 11 (depends on 10) The method of claim 10, wherein the thermostat includes a rechargeable battery and the first processor is configured to transition between a wake state and a sleep state, and wherein the method further comprises re-determining the parameterized model and/or optimal radiant heat control strategy each time the first processor transitions from the sleep state to the wake state, the parameterized model and/or optimal radiant heat control strategy being re-determined based at least in part on ambient temperature readings determined by the second processor during the sleep state of the first processor. ### Claim 12 (depends on 8) The method of claim 8, wherein each candidate radiant heating control strategy is binary-valued. ### Claim 13 (depends on 8) The method of claim 8, further comprising: determining a first optimal radiant heat strategy covering a first time period; executing the first optimal radiant heat strategy to control the radiant heating system during the first time period; determining a second optimal radiant heat control strategy during the first time period; and executing the second optimal radiant heat strategy prior to an end of the first time period to control the radiant heating system. ### Claim 14 (depends on 8) The method of claim 8, further comprising determining a Lag value that represents at least in part an amount of system inertia for the enclosure. ### Claim 15 A computer-program product, tangibly embodied in a non-transitory machine readable storage medium, including instructions configured to cause a data processing apparatus of a thermostat to: determine a parameterized model from which a temperature response of an enclosure responsive to a candidate radiant heating control strategy may be determined, the parameterized model being based at least in part on historical temperature information stored in memory and acquired during at least one historical period in which the enclosure was heated by a radiant heating system under the control of the thermostat; determine an optimal radiant heating control strategy from among a plurality of candidate radiant heating control strategies by using said parameterized model to compute a plurality of predicted temperature responses corresponding respectively to the plurality of candidate radiant heating control strategies and processing said predicted temperature responses according to one or more predetermined assessment criteria; and control the radiant heating system according to the determined optimal radiant heating control strategy. ### Claim 16 (depends on 15) The computer-program product of claim 15, wherein the memory is disposed within a housing of the thermostat, and wherein one or more temperature sensors are also disposed within the housing. ### Claim 17 (depends on 16) The computer-program product of claim 16, wherein the data processing apparatus of the thermostat includes a first relatively high-powered processor that is configured and programmed to determine the parameterized model and to determine the optimal radiant heating control strategy by computing the plurality of predicted temperature responses, and wherein the data processing apparatus includes a second relatively low-powered processor that is in operative communication with the one or more temperature sensors to determine an ambient temperature of the enclosure. ### Claim 18 (depends on 17) The computer-program product of claim 17, wherein the thermostat includes a rechargeable battery and the first processor is configured to transition between a wake state and a sleep state, and wherein the instructions are further configured to cause the data processing apparatus to re-determine the parameterized model and/or optimal radiant heat control strategy each time the first processor transitions from the sleep state to the wake state, the parameterized model and/or optimal radiant heat control strategy being re-determined based at least in part on ambient temperature readings determined by the second processor during the sleep state of the first processor. ### Claim 19 (depends on 15) The computer-program product of claim 15, wherein each candidate radiant heating control strategy is binary-valued. ### Claim 20 (depends on 15) The computer-program product of claim 15, wherein the instructions are further configured to cause the data processing apparatus to: determine a first optimal radiant heat strategy covering a first time period; execute the first optimal radiant heat strategy to control the radiant heating system during the first time period; determine a second optimal radiant heat control strategy during the first time period; and execute the second optimal radiant heat strategy prior to an end of the first time period to control the radiant heating system.