Abstract: Disclosed is a system and method for managing the comfort of building occupants. The system utilizes a model-based approach for targeting occupant comfort levels. The system allows for voting input from building occupants regarding their respective comfort. Additionally, the system provides a user interface to gather occupant input and use said input as a parameter in a comfort model.

Abstract: Apparatuses, systems, methods, and computer program products are presented for a building-automation system controller. A building-automation system controller manages and/or controls energy, thermal, and/or functional systems and subsystems thereof utilizing a sensor, a physical model, a simulation engine, one or more predictive control loops, an optimal cost function, and an error band. A control loop is designed to utilize a simulation engine to predict a simulated predicted sensor value of a controlled system under a simulated control regime. A simulated control regime having an optimal cost function is selected for a controlled system until the controlled system diverges from the simulated predicted sensor value beyond an error band indicating uncertainty in a predicted future behavior so that a control loop is formed utilizing a simulation engine to predict a different future behavior in response to the controlled system diverging from the simulated predicted sensor value.

Abstract: Disclosed is a system and method for classifying units of control and concomitant model units from a larger physical system model. The system enables model-based simulation of decoupled system units for improved simulation efficiency. Further, the system allows for automated reasoning about the classification of said units, producing both machine-interpretable and human-readable, natural language descriptions of the decisions and reasons for said decisions made during the classification process, for use in heuristics and user feedback.

Abstract: Apparatuses, systems, and methods of physical-model based building automation using in-situ regression to optimize control systems are presented. A simulation engine is configured to simulate a behavior or a controlled system using a physical model for the controlled system. A data stream comprises data from a controlled system. A training loop is configured to compare an output of a simulation engine to a data stream using a heuristic so that a physical model is regressed in a manner that the output of the simulation engine approaches the data stream.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for organizing automatic control in automation systems from a system description, using deconstruction of complex equipment graphs. A system control scheme is automatically generated from a deconstruction of an equipment graph into controllable sets of prioritized sub-systems. An equipment graph comprises one or more subsystems of equipment. Prioritized sub-systems comprise a unique routing path through an equipment graph. Prioritized sub-systems comprise the ability to be actuated and are divided into groups of sub-system sets. Groups of sub-system sets comprise synchronous and asynchronous sets and are created for conjoined routing paths of parallel sub-systems.

Abstract: Apparatuses, systems, and methods of physical-model based building automation using in-situ regression to optimize control systems are presented. A simulation engine is configured to simulate a behavior or a controlled system using a physical model for the controlled system. A data stream comprises data from a controlled system. A training loop is configured to compare an output of a simulation engine to a data stream using a heuristic so that a physical model is regressed in a manner that the output of the simulation engine approaches the data stream.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for organizing automatic control in automation systems from a system description, using deconstruction of complex equipment graphs. A system control scheme is automatically generated from a deconstruction of an equipment graph into controllable sets of prioritized sub-systems. An equipment graph comprises one or more subsystems of equipment. Prioritized sub-systems comprise a unique routing path through an equipment graph. Prioritized sub-systems comprise the ability to be actuated and are divided into groups of sub-system sets. Groups of sub-system sets comprise synchronous and asynchronous sets and are created for conjoined routing paths of parallel sub-systems.

Abstract: Disclosed is a building-automation system controller for management and control of energy, thermal, and functional systems and subsystems thereof utilizing predictive control loops utilizing time-based simulation acting upon the atomic control unit triad of source-transport-sink.

Abstract: Disclosed is a method of physical-model based building automation using in-situ regression to optimize control systems.

Abstract: Disclosed is a method of organizing automatic control in automation systems from a system description, using deconstruction of complex equipment graphs.