Invensys Systems, Inc.

Aveva Software, LLC

Schneider Electric Software, LLC

Alan Bee Morrow

Thomas B Kinney

Donald E Labbe

Lewis Gordon

Andrew Speziale

Randy Dwiggins

Fayyaz Hussain

Paul Kesseler

Disclosed are systems, servers and methods for improving temperature profile control in a reactor with at least three fixed beds, exothermic reactions and interstage cooling. A model of the temperature differential across the first bed is developed and its error is used to infer unmeasured feed composition disturbances, which are used in the control of the downstream fixed beds for faster response to unmeasured feed composition changes and improved control of the temperature profile throughout the reactor. The first bed model error is then used as an input into an overall model that predicts reactor temperature profiles, which provides advanced notice of reactions in downstream beds, and enables efficient adjustment and compensation to a feed composition change. A Model Predictive Control (MPC) algorithm is applied to adjust the bed intercooling and first bed feed temperature so that the reactor temperature profile can be more precisely controlled.

Computerized systems and methods for temperature profile control in a reactor with a series of fixed beds

Controlling and optimizing industrial processes by integrating MPC-based approaches and expert system approaches. At least two different control variables with identical models are used. An expert system adjusts at least one of the control variables to change a setpoint or range or the like while standard MPC techniques change another control variable to address appropriate classes of control problems.

Integrated model predictive control and advanced process control

A multivariable control system for controlling boiler burners. The system includes burner actuators, boiler sensors, a control system coupled to the actuators and the sensors and further includes a memory and a processor, and an application stored in the memory. When executed by the processor, the application executes a multivariable control algorithm to determine actuator manipulated variable values to control in part the burners based on data received from the sensors and based on a plurality of gain values. The application also executes an adaptation algorithm to change an actuator manipulated variable value, to maintain the changed manipulated variable value for a pre-determined period of time, to determine a change in data received from the sensors, to determine a gain value based on the changed manipulated variable value and the change in data received from the sensors, and to provide the determined gain value to the multivariable control algorithm.

Smart firing control in a rankine cycle power plant

Methods and systems for controlling a cement finishing mill, and operating the mill at an optimal point, are disclosed. To determine an optimal point of operation, values of mill power and sound are collected and compared to values predicted by a model to determine if the mill is choking. This choking determination is used in one of two processes to determine an optimal point of operation for the mill. In the first process, as long as the mill is not choking, the amount of fresh feed input to the mill is incrementally increased; when choking occurs, the amount of fresh feed is decreased until choking ceases. In the second process, the amount of fresh feed input to the mill is increased and decreased in an oscillating manner over time, to find the amount of feed that results in the mill approaching, but never reaching, a choking state.

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Cumberland, RI, United States of America

Alan Bee Morrow