Exxonmobil Research and Engineering Company

Exxonmobil Upstream Research Company

Thomas A Badgwell

Frank Hershkowitz

Paul Joseph Berlowitz

Timothy Andrew Barckholtz

Krishnan Kumaran

Paul E Pastusek

Wei D Liu

Niranjan A Subrahmanya

Kuang-Hung Liu

Sandipan K Das

David J Schmidt

Michael H Kovalski

A method and controller system are described for automatically tuning a controller of a drilling rig. The controller system includes a controller that determines a moving average of measured values, determines a moving standard deviation of the measured values, defines an outer zone of measured values with the determined moving average and the determined moving standard deviation, defines an inner zone of measured values with the determined moving average and the determined moving standard deviation, monitors the measured values for the occurrence of statistical events with respect to the outer zone and inner zone. Based on the detected statistical event, the controller adjusts the gain of the controller the based on the statistical event being associated with the outer zone or inner zone.

Controller with automatic tuning and method

Systems and methods are provided for using a Deep Reinforcement Learning (DRL) agent to provide adaptive tuning of process controllers, such as Proportional-Integral-Derivative (PID) controllers. The agent can monitor process controller performance, and if unsatisfactory, can attempt to improve it by making incremental changes to the tuning parameters for the process controller. The effect of a tuning change can then be observed by the agent and used to update the agent's process controller tuning policy. It has been unexpectedly discovered that providing adaptive tuning based on incremental changes in tuning parameters, as opposed to making changes independent of current values of the tuning parameters, can provide enhanced or improved control over a controlled variable of a process.

Adaptive PID controller tuning via deep reinforcement learning

Systems and methods are provided for arranging processing units in a common volume to allow for processing of a fluid flow as part of a mass and/or heat transfer process. Fuel cells are examples of processing units that include separate flow paths for processing two input fluid flows with mass and/or heat transfer between the separate flow paths. The arrangements described herein can allow a gas phase fluid flow to be delivered to a first process flow path of processing units in a common volume. The gas phase fluid flow can be delivered in a relatively uniform manner without the use of an intervening manifold to distribute gas from the common volume into the processing units.

Housing for multiple fuel cell stacks

In various aspects, systems and methods are provided for integrating molten carbonate fuel cells with a fired heater for production of electrical power while also reducing or minimizing the amount of COpresent in the flue gas generated by the fired heater. The molten carbonate fuel cells can be integrated for use with fired heater so that at least a portion of the flue gas from fired heater flows through cathodes of the fuel cells and at least a portion of the cathode exhaust is returned to a convection section of the fired heater.

Low-emission fired heater

Growing community of inventors

Clinton, NJ, United States of America

Thomas A Badgwell