Fisher-Rosemount Systems, Inc

Vasiliki Tzovla

Mark J Nixon

Terrence L Blevins

Larry Oscar Jundt

Wilhelm K Wojsznis

Kent Allan Burr

Dennis L Stevenson

Andrew Philip Dove

Neil J Peterson

Dan Dean Christensen

Steve Dienstbier

Dirk Thiele

Ashish Mehta

Sai Ganesamoorthi

A process control routine may include a first internal function block for executing a control operation based on an input signal and an information conduit communicatively connected to the first internal function block. The information conduit may have an output adapted to provide the input signal to the first internal function block. The process control routine may further include an external function block communicatively connected to the information conduit and adapted to generate the input signal such that the output signal is directly provided to the information conduit prior to the execution of the control operation.

Shadow function block interface for use in a process control network

A portable computer for use in interfacing to a process control system having a host system includes a housing adapted for hand-held operation, a processing unit disposed within the housing and a computer readable memory disposed within the housing and coupled to the processing unit. The portable computer also includes a display, a keypad and a radio frequency transceiver adapted to communicate with the host system, all of which are disposed within the housing and communicatively coupled to the processing unit. A first software routine stored in the computer readable memory processes a user input received from the keypad and sends a command to the host system via the radio frequency transceiver. Additionally, a second software routine stored in the computer readable memory receives process information sent from the host system in response to the command and displays the received process information via the portable computer display.

Portable computer in a process control environment

An adaptive predictive model includes a standard predictive model, such as a neural network or a natural model, constructed to produce an output that predicts a process parameter and a combiner network that combines the output of the predictive model with one or more measured values of the process parameter to produce an adjusted predicted process parameter during operation of a process. The adaptive predictive model reduces or corrects for non-linear as well as linear errors in the prediction of a process variable without having to reform the predictive model itself, while requiring only minor increases in processing power and time.

Adaptive predictive model in a process control system

A process controller that is communicatively coupled to an external field device via a communication network uses a shadow function block disposed within a process controller to enable implementation of a control routine that uses both an internal function block disposed within the process controller and an external function block disposed within the external field device. The shadow function block includes a communication port that communicates with the external function block via the communication network to thereby receive data pertaining to the external function block, a memory that stores the received data according to a configuration protocol of the internal function block and an output that provides the stored external function block data to the internal function block according to the configuration protocol of the internal function block. The communication port of the interface function block may include an output that sends data generated by the controller or the internal function block to the external function block using the communication protocol associated with the external function block.

An advanced control block that implements multiple-input/multiple-output control, such as model predictive control, within a process control system is initiated by creating an initial control block having generic control logic and desired control inputs and control outputs communicatively connected to process outputs and process inputs within a process control routine. A waveform generator within the control block systematically upsets each of the process inputs via the control block outputs using excitation waveforms designed for use in developing a process model. At the same time, a data collection routine collects data indicating the response of each of the process outputs to the waveforms delivered at each of the process inputs. After sufficient data has been collected, a process modeling routine generates a process model from the collected data and a control logic parameter creation routine creates control logic parameters for the control logic from the process model. The control logic parameters and the process model are then downloaded to the control block to complete formation of the advanced control block. Thereafter, the advanced control block is used to provide advanced process control within the process control routine. Likewise, the process model is used to provide simulation of the process or to produce virtual process outputs.

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Austin, TX, United States of America

Vasiliki Tzovla