Abstract: An apparatus for controlling an operation of a system is provided. The apparatus comprises an input interface configured to receive a state trajectory of the system, and a memory configured to store a model of dynamics of the system including a combination of at least one differential equation and a closure model. The apparatus further comprises a processor configured to update the closure model using reinforcement learning (RL) having a value function reducing a difference between a shape of the received state trajectory and a shape of state trajectory estimated using the model with the updated closure model, and determine a control command based on the model with the updated closure model. Further, the apparatus comprises an output interface configured to transmit the control command to an actuator of the system to control the operation of the system.

Abstract: A system a method for controlling an operation of HVAC system is provided. The system comprises at least one processor; and memory having instructions stored thereon that, when executed by the at least one processor, cause the system to receive data indicative of the operation of the HVAC system and optimize a cost function to reduce a difference between a full thermal state of the conditioned environment simulated from the received data based on a physical model of airflow including a partial differential equation (PDE) and a thermal state of the conditioned environment reconstructed by an observer using a reduced order model (ROM) of airflow including an ordinary differential equation (ODE) from values of the full thermal state at a set of locations, wherein optimization of the cost function is a multivariable optimization of a structure of the observer and a structure of the ODE.

Abstract: A computer-implemented method using a reinforcement learning trained reduced order estimator (RL-trained ROE) and a closure model is provided for controlling a heating, ventilation, and air conditioning (HVAC) system including actuators. The method uses a processor coupled with a memory storing instructions implementing the method, wherein the instructions, when executed by the processor, carry out at steps of the method, includes acquiring setpoints of the HVAC system from a user input and measurement data from sensors arranged in the HVAC system, computing a high-dimensional state estimate using the measurement data and an estimate of reduced-order state from the RL-trained ROE, determining a controller with respect to the setpoints by using the RL-trained ROE, generating control commands based on the controller, and transmitting the control commands to the actuators of HVAC system via an output interface.

Abstract: A control system for controlling a heating ventilation and air conditioning (HVAC) system, uses a thermal comfort model (TCM), an airflow dynamics model (ADM) and an HVAC model connecting thermal states at air vents with states of actuators of the HVAC system, for determining a target thermal state at the air vents connecting the HVAC system to an environment, such that the target thermal state at the air vents results in a thermal state at the location of an occupant according to the ADM connecting uneven distribution of thermal states at different locations in the environment. Further, the control system determines and submits control commands to one or multiple actuators of the HVAC system producing the target thermal state at the air vents.

Abstract: A computer-implemented method is provided. The computer-implemented includes a data-driven model and a robust closure model stored in a memory by using a processor for controlling a system. The computer-implemented method includes steps of acquiring sensor signals from at least one sensor of the system via an interface, computing a state of the system based on the sensor signals, determining a gain of the robust closure model based on the state of the system, reproducing a state of the system based on the determined gain, estimating a physics-based model of the system by combining the data-driven model and the robust closure model, and generating control commands by mapping the state of the system using the estimated physics-based model.

Abstract: The present disclosure provides a system and a method for detecting a fault of an operation of a synchronous motor. The method includes collecting an electrical input and measurements associated with the operation of the synchronous motor caused by the electrical input. The method further includes determining sequences of points defining a mutual position between a stator and a rotor of the synchronous motor that results in magnetostatic determined as a weighted summation over real-space basis functions parameterized on pairs of adjoint points in the determined sequence of points and weighted with a surface charge density between corresponding adjoint points, such that the resulted magnetostatic explains the measurements of the operation of the synchronous motor given the electrical input. Further, the method includes determining the fault of the operation of the synchronous motor based on the mutual position between the stator and the rotor of the synchronous motor.

Abstract: A simulation system for designing a heating ventilation and air conditioning (HVAC) system is provided. The system comprises an input interface configured to accept thermal data indicative of a target distribution of thermal state and environmental data, and a memory configured to store a building envelope model (BEM), an airflow dynamics model (ADM), and an HVAC model. The simulation system further comprises a processor configured to process the environmental data with the BEM to estimate thermal state of the air at the walls of the environment, and determine one or more design variables, by minimizing a multi-objective cost function. The simulation system further comprises an output interface configured to output the one or more design variables.

Abstract: A computer-implemented method is provided. The computer-implemented includes a data-driven model and a robust closure model stored in a memory by using a processor for controlling a system. The computer-implemented method includes steps of acquiring sensor signals from at least one sensor of the system via an interface, computing a state of the system based on the sensor signals, determining a gain of the robust closure model based on the state of the system, reproducing a state of the system based on the determined gain, estimating a physics-based model of the system by combining the data-driven model and the robust closure model, and generating control commands by mapping the state of the system using the estimated physics-based model.

Abstract: A system a method for controlling an operation of HVAC system is provided. The system comprises at least one processor; and memory having instructions stored thereon that, when executed by the at least one processor, cause the system to receive data indicative of the operation of the HVAC system and optimize a cost function to reduce a difference between a full thermal state of the conditioned environment simulated from the received data based on a physical model of airflow including a partial differential equation (PDE) and a thermal state of the conditioned environment reconstructed by an observer using a reduced order model (ROM) of airflow including an ordinary differential equation (ODE) from values of the full thermal state at a set of locations, wherein optimization of the cost function is a multivariable optimization of a structure of the observer and a structure of the ODE.

Abstract: A wind flow sensing system for determining a turbulence of wind flow at a set of different altitudes above a terrain is provided. The wind flow sensing system comprises an input interface configured to receive a set of measurements of radial velocities at line-of-site points above the terrain for each of the altitudes for a set of time steps, and a processor configured to estimate velocity fields for each of the altitudes based on data assimilation of the velocity fields, estimate unbiased horizontal velocities at each of the altitudes and for each time step, determine an average of the unbiased horizontal velocities for a period of time including the set of time steps, and determine, at each of the altitudes, a turbulence based on the unbiased horizontal velocities for each time step and the average of the unbiased horizontal velocity.

Abstract: A wind flow sensing system for determining wind flow at a set of different altitudes above a terrain is provided, The wind flow sensing system comprises an input interface configured to receive a set of measurements of radial velocities at line-of-site points above the terrain for each of the altitudes, and a processor configured to estimate velocity fields for each of the altitudes based on data assimilation of the velocity fields above an approximation of the shape of the terrain with a set of one or multiple convex shapes to fit the measurements of radial velocities and estimate horizontal velocities at each of the altitudes as a horizontal projection of the corresponding radial velocities corrected with corresponding horizontal derivatives of vertical velocities of the estimated velocity fields. The wind flow sensing system further comprises an output interface configured to render the estimated horizontal velocities at each of the altitudes.

Abstract: A control system for controlling an operation of a heating ventilation and air conditioning (HVAC) system is provided. The control system comprises an input interface configured to accept data indicative of a target distribution of thermal state in an environment, and a memory configured to store an airflow dynamics model (ADM) and an HVAC model. The control system further comprises a processor configured to inverse the ADM to estimate values of boundary conditions for inlet locations defining target thermal state at the inlet locations that result in the target distribution of thermal state in the environment; determine, using the HVAC model, target control parameters of actuators of the HVAC system resulting in the target thermal state at the inlet locations; and submit control commands to the HVAC system to operate the actuators of the HVAC system according to the control parameters.

Abstract: A wind flow sensing system for determining a turbulence of wind flow at a set of different altitudes above a terrain is provided. The wind flow sensing system comprises an input interface configured to receive a set of measurements of radial velocities at line-of-site points above the terrain for each of the altitudes for a set of time steps, and a processor configured to estimate velocity fields for each of the altitudes based on data assimilation of the velocity fields, estimate unbiased horizontal velocities at each of the altitudes and for each time step, determine an average of the unbiased horizontal velocities for a period of time including the set of time steps, and determine, at each of the altitudes, a turbulence based on the unbiased horizontal velocities for each time step and the average of the unbiased horizontal velocity.

Abstract: A wind flow sensing system for determining wind flow at a set of different altitudes above a terrain is provided, The wind flow sensing system comprises an input interface configured to receive a set of measurements of radial velocities at line-of-site points above the terrain for each of the altitudes, and a processor configured to estimate velocity fields for each of the altitudes based on data assimilation of the velocity fields above an approximation of the shape of the terrain with a set of one or multiple convex shapes to fit the measurements of radial velocities and estimate horizontal velocities at each of the altitudes as a horizontal projection of the corresponding radial velocities corrected with corresponding horizontal derivatives of vertical velocities of the estimated velocity fields. The wind flow sensing system further comprises an output interface configured to render the estimated horizontal velocities at each of the altitudes.

Abstract: An apparatus for controlling an operation of a system is provided. The apparatus comprises an input interface configured to receive a state trajectory of the system, and a memory configured to store a model of dynamics of the system including a combination of at least one differential equation and a closure model. The apparatus further comprises a processor configured to update the closure model using reinforcement learning (RL) having a value function reducing a difference between a shape of the received state trajectory and a shape of state trajectory estimated using the model with the updated closure model, and determine a control command based on the model with the updated closure model. Further, the apparatus comprises an output interface configured to transmit the control command to an actuator of the system to control the operation of the system.

Abstract: A control system for controlling an operation of a heating ventilation and air conditioning (HVAC) system is provided. The control system comprises an input interface configured to accept data indicative of a target distribution of thermal state in an environment, and a memory configured to store an airflow dynamics model (ADM) and an HVAC model. The control system further comprises a processor configured to inverse the ADM to estimate values of boundary conditions for inlet locations defining target thermal state at the inlet locations that result in the target distribution of thermal state in the environment; determine, using the HVAC model, target control parameters of actuators of the HVAC system resulting in the target thermal state at the inlet locations; and submit control commands to the HVAC system to operate the actuators of the HVAC system according to the control parameters.

Abstract: A simulation system for designing a heating ventilation and air conditioning (HVAC) system is provided. The system comprises an input interface configured to accept thermal data indicative of a target distribution of thermal state and environmental data, and a memory configured to store a building envelope model (BEM), an airflow dynamics model (ADM), and an HVAC model. The simulation system further comprises a processor configured to process the environmental data with the BEM to estimate thermal state of the air at the walls of the environment, and determine one or more design variables, by minimizing a multi-objective cost function. The simulation system further comprises an output interface configured to output the one or more design variables.

Abstract: A control system for controlling a heating ventilation and air conditioning (HVAC) system, uses a thermal comfort model (TCM), an airflow dynamics model (ADM) and an HVAC model connecting thermal states at air vents with states of actuators of the HVAC system, for determining a target thermal state at the air vents connecting the HVAC system to an environment, such that the target thermal state at the air vents results in a thermal state at the location of an occupant according to the ADM connecting uneven distribution of thermal states at different locations in the environment. Further, the control system determines and submits control commands to one or multiple actuators of the HVAC system producing the target thermal state at the air vents.

Abstract: A wind flow sensing system determines a first approximation of the velocity field at each of the altitudes by simulating computational fluid dynamics (CFD) of the wind flow with operating parameters reducing a cost function of a weighted combination of errors, determines a horizontal derivative of vertical velocity at each of the altitudes from the first approximation of the velocity fields, and determines a second approximation of the velocity fields using geometric relationships between a velocity field for each of the altitudes, projections of the measurements of radial velocities on the three-dimensional axes, and the horizontal derivative of vertical velocity for the corresponding velocity field. In the cost function of the CFD, each error corresponds to one of the altitudes and includes a difference between measured velocities at the line-of-site points at the corresponding altitude and simulated velocities at the line-of-site points simulated by the CFD for the corresponding altitude.

Abstract: A wind flow sensing system determines a first approximation of the velocity field at each of the altitudes by simulating computational fluid dynamics (CFD) of the wind flow with operating parameters reducing a cost function of a weighted combination of errors, determines a horizontal derivative of vertical velocity at each of the altitudes from the first approximation of the velocity fields, and determines a second approximation of the velocity fields using geometric relationships between a velocity field for each of the altitudes, projections of the measurements of radial velocities on the three-dimensional axes, and the horizontal derivative of vertical velocity for the corresponding velocity field. In the cost function of the CFD, each error corresponds to one of the altitudes and includes a difference between measured velocities at the line-of-site points at the corresponding altitude and simulated velocities at the line-of-site points simulated by the CFD for the corresponding altitude.