Embodiments include a computer-implemented method (and system) for performing automated batch data alignment for modeling, monitoring, and control of an industrial batch process. The method (and system) loads, scales, and screens plant historian batch data for an industrial batch process. The method (and system) selects a reference batch as basis of the batch alignment, defines and adds or modifies one or more batch phases, and selects one or more batch variables based on one or more profiles and corresponding curvatures of the batch data. The method (and system) estimates one or more weightings, adjust one or more tuning parameters and uses a sliding time window combined with DTW, DTI and GSS algorithms, performs the batch alignment in offline mode or online mode.

Systems and methods are described herein are directed to determining optimal operating set points in sync with dynamic demand responsive to time-varying events in a data center. The method includes establishing, by a matrix module executing on a computing device, a data matrix of a first set of critical data based on resources in the data center representing dynamic demand, the dynamic demand responsive to the time-varying events in the data center. A decomposition module can generate new critical data based in part on the first set of critical data. A prediction module can determine optimal operating set points using the new critical data. The optimal operating set points for the resources can be transmitted by a communications module to a data center orchestration unit such as a building management module.

Controlling flow of gas in a gas pipeline network, wherein flow of gas within each of the pipeline segments is associated with a direction (positive or negative). Processors calculate minimum and maximum production rates (bounds) at the gas production plant to satisfy an energy consumption constraint over a period of time. The production rate bounds are used to calculate minimum and maximum signed flow rates (bounds) for each pipeline segment. A nonlinear pressure drop relationship is linearized to create a linear pressure drop model for each pipeline segment. A network flow solution is calculated, using the linear pressure drop model, comprising flow rates for each pipeline segment to satisfy demand constraints and pressures for each of a plurality of network nodes over the period of time to satisfy pressure constraints. The network flow solution is associated with control element setpoints used to control one or more control elements.

A method for devising an optimum control policy of a controller for controlling a system includes optimizing at least one parameter that characterizes the control policy. A Gaussian process model is used to model expected dynamics of the system. The optimization optimizes a cost function which depends on the control policy and the Gaussian process model with respect to the at least one parameter. The optimization is carried out by evaluating at least one gradient of the cost function with respect to the at least one parameter. For an evaluation of the cost function a temporal evolution of a state of the system is computed using the control policy and the Gaussian process model. The cost function depends on an evaluation of an expectation value of a cost function under a probability density of an augmented state at time steps.

An edge platform of a building communicatively coupled to a cloud system, the edge platform including one or more memory devices having instructions stored thereon and one or more processors executing the instructions causing the one or more processors to receive an event from a piece of building equipment of the building, the event indicating a data value associated with the piece of building equipment occurring at a particular time, identify contextual data of a data structure that provides a contextual description of the event, generate an enriched event by enriching the event with the contextual data, the enriched event including the data value, the particular time, and the contextual data, and communicate the enriched event to the cloud system configured to operate based on the enriched event.

A building system of a building including one or more memory devices having instructions thereon, that, when executed by one or more processors, cause the one or more processors to manage a plurality of entitlements for a plurality of subscriptions of one or more buildings with a building entitlement model, receive a first request to perform a first operation for a first subscription and a second request to perform a second operation for a second subscription, and implement the first operation on first computing resources of a first zone based on the building entitlement model in response to a first determination that the first subscription has the first entitlement and implement the second operation on second computing resources of the second zone based on the building entitlement model in response to a second determination that the second subscription has the second entitlement.

The embodiments described herein include one embodiment that a control method including executing an infeasible search algorithm during a first portion of a predetermined sample period to search for a feasible control trajectory of a plurality of variables of a controlled process, executing a feasible search algorithm during a second portion of the predetermined sample period to determine the feasible control trajectory if the infeasible search algorithm does not determine a feasible control trajectory, and controlling the controlled process by application of the feasible control trajectory.

A control device for a technical process, having at least two devices for detecting a respective input signal and at least one manipulated variable output device. The output device forms a difference between a reference variable and a controlled variable and ascertains a manipulated variable therefrom. The control device additionally has at least one internal signal processing system for influencing the time response and damping behavior of a control loop formed by the control device and technical process. At least two filter devices provide signal processing. A first filter device interacts with the process such that the control loop time response can be influenced by a filter device property change, and at least one amplification element interacts such that the control loop damping behavior can be influenced by an amplification element amplification factor change and such that the second filter device and the I element can be activated individually.

Provided an active suppression controller with an adaptive algorithm capable of tracking the fluctuation of multi-fundamental frequencies and correcting them while the deviation is divergence based on the DXHS (Delayed-X Harmonics Synthesizer). It includes a controller's architecture, an adaptive frequency tracking & correcting algorithm and its FPGA implementation structure in real-time.

A tuning method is to provide a tuning system equipped with a virtual machine which is modeled after a target machine, set the processing conditions of the target machine into the tuning system, enter a simulation command containing simulation parameters into the virtual machine, subject the virtual machine to simulate the response of the target machine according to the simulation parameters to calculate required control parameters, and use the control parameters as the base parameters for adjusting the target machine.