A first valve of a manifold for a fluid distribution system may regulate a fluid flow to a first fluid handling device (“FHD”). A second valve of the manifold may communicate with a second FHD, a reservoir, or a recirculation line. A target flow condition for the manifold may be determined by a manifold control system (“MCS”) based on a device setting received for the first FHD. The MCS may determine a fluid distribution system operation for obtaining the target flow condition based on the target flow condition, a flowrate of the fluid flow, and an operational state of a supply device. The operation may include the MCS controlling at least one of the supply device, the first valve, and the second valve to change the flowrate. The MCS may continuously operate at least one manifold valve to maintain the target flow condition once exhibited by the manifold.

A first valve of a manifold for a fluid distribution system may regulate a fluid flow to a first fluid handling device (“FHD”). A second valve of the manifold may communicate with a second FHD, a reservoir, or a recirculation line. A target flow condition for the manifold may be determined by a manifold control system (“MCS”) based on a device setting received for the first FHD. The MCS may determine a fluid distribution system operation for obtaining the target flow condition based on the target flow condition, a flowrate of the fluid flow, and an operational state of a supply device. The operation may include the MCS controlling at least one of the supply device, the first valve, and the second valve to change the flowrate. The MCS may continuously operate at least one manifold valve to maintain the target flow condition once exhibited by the manifold.

A method of controlling a nuclear power plant includes obtaining sensor data from one or more sensors of the nuclear power plant, providing the sensor data and a desired plant response to a neural network, wherein the neural network has been previously trained using a simulated nuclear power plant and is structured to determine at least one control system setting to achieve the desired plant response, determining at least one control system setting to achieve the desired plant response with the neural network, and setting or changing at least one control system setting of a control system of the nuclear power plant to the at least one control system setting determined by the neural network.

A system and method for controlling operations of a fluid distribution may include a first manifold receiving a next mode of operation for the fluid distribution system. The first manifold may calculate first and second flow requirements for the first and second manifolds that may respectively include a first and second total flowrates from the first and second manifolds. The first manifold may determine required operation states for valves of the first manifold and the second manifold for the next mode based on the first and second flow requirements. The first manifold may be controllably operated to cause the second manifold and a supply device of the fluid distribution system to operate in the required operation states and provide first and second flow requirements. The first manifold may direct the second manifold to independently balance individual outlet flowrates of the second manifold while continuing to provide the second flow requirements.

A system and method for controlling operations of a fluid distribution may include a first manifold receiving a next mode of operation for the fluid distribution system. The first manifold may calculate first and second flow requirements for the first and second manifolds that may respectively include a first and second total flowrates from the first and second manifolds. The first manifold may determine required operation states for valves of the first manifold and the second manifold for the next mode based on the first and second flow requirements. The first manifold may be controllably operated to cause the second manifold and a supply device of the fluid distribution system to operate in the required operation states and provide first and second flow requirements. The first manifold may direct the second manifold to independently balance individual outlet flowrates of the second manifold while continuing to provide the second flow requirements.

A servo control device to execute an operation in a discrete time system may include a velocity feedback path having a difference means calculating a pseudo-velocity from a detected position and a lowpass filter, and a PI control means executing a proportional integration control operation on a deviation between the pseudo-velocity and the position deviation to create a drive command for the driver. The velocity feedback path includes a first gain means applying a first gain to the pseudo-velocity, a delay means delaying the pseudo-velocity, and a second gain means applying a second gain to the delayed pseudo-velocity. A sum of an output of the first gain means and the second gain means is inputted to the lowpass filter, and “F.sub.a(z)=1/(1−z.sup.−1F.sub.b(z))” is satisfied where a transfer function of the PI control means is F.sub.a(z), and a transfer function of the lowpass filter is F.sub.b(z).

A control customization system 80 customizes a plant control. A profiler 81 predicts actions of a user depending on situations of the plant or the user. A planner 82 determines an appropriate set of objectives which represent tasks desired by the user, and objective terms representing elements for controlling the plant so as to realize the objectives, and tunes the objective terms based on predictions of the profiler 81.

A system for controlling an operation of a machine including a plurality of actuators assisting one or multiple tools to perform one or multiple tasks, in response to receiving an acoustic mixture of signals generated by the tool performing a task and by the plurality of actuators actuating the tool, submit the acoustic mixture of signals into a neural network trained to separate from the acoustic mixture a signal generated by the tool performing the task from signals generated by the actuators actuating the tool to extract the signal generated by the tool performing the task from the acoustic mixture of signals, analyze the extracted signal to produce a state of performance of the task, and execute a control action selected according to the state of performance of the task.

An intelligent control system and method of thin plate dryer for cut tobacco are provided. The system includes a factor searching and screening unit, a control unit, an early warning unit. The control unit adopts a dual-model control method and establishes a process parameter control model and an energy balance model, the control unit calculates the moisture discharge opening value in real time according to the dual-model; the early warning unit is configured to connected with the control unit, and send out an alarm information based on early warning signal. The present disclosure is designed to transform the traditional control into intelligent precision control, improve product quality, reduce product differences between batches and build an intelligent early warning function.

An information processing apparatus incudes a schedule determination unit configured to determine a schedule of an operating status for causing a temperature of an air-conditioned space of each of a plurality of load-side units to reach a specified set temperature at a specified set time, based on a learning model representing an input-output relationship between input data indicating an influencing factor of a thermal load of each of the load-side units and output data indicating the thermal load.