Method and apparatus for artificially intelligent model-based control of dynamic processes using probabilistic agents
First Claim
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1. A method for controlling a process of at least one device, the method comprising:
- receiving real time process data generated from the process;
processing the real time process data, and comparing the processed data against at least one reference of a process model of the process for establishing any deviation from normal operation;
classifying, at a status agent, a source of the deviation and a likely cause of the deviation;
prioritizing actuation of one or more diagnostic agents related to the causality of the deviation at a supervisory manager;
actuating the one or more diagnostic agents;
communicating the results of the diagnostic agents to the supervisory manager;
modifying, under the instruction of the supervisory manager, the process model based on the results of the one or more diagnostic agents, if the source of the deviation is the process model; and
applying, under the instruction of the supervisory manager, the process model at a control agent for evaluating risk and recommending and initiating at least one control action to control the process of the at least one device.
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Abstract
A system and method for controlling a process such as an oil production process is disclosed. The system comprises multiple intelligent agents for processing data received from a plurality sensors deployed in a job site of an oil well, and applies a probabilistic model for evaluating risk and recommending appropriate control action to the process.
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Citations
27 Claims
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1. A method for controlling a process of at least one device, the method comprising:
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receiving real time process data generated from the process; processing the real time process data, and comparing the processed data against at least one reference of a process model of the process for establishing any deviation from normal operation; classifying, at a status agent, a source of the deviation and a likely cause of the deviation; prioritizing actuation of one or more diagnostic agents related to the causality of the deviation at a supervisory manager; actuating the one or more diagnostic agents; communicating the results of the diagnostic agents to the supervisory manager; modifying, under the instruction of the supervisory manager, the process model based on the results of the one or more diagnostic agents, if the source of the deviation is the process model; and applying, under the instruction of the supervisory manager, the process model at a control agent for evaluating risk and recommending and initiating at least one control action to control the process of the at least one device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 17, 18, 19, 20, 21, 22, 23)
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8. A method of controlling a process comprising:
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comparing real time data to at least one reference of a process model of the process, said comparing taking into account operational variance and thereby identifying deviations; tracking the process and the specific states thereof; monitoring and identifying variations of the process from normal operation, and generating outputs; based on said outputs, classifying one or more diagnoses relevant to the deviations; prioritizing the classified diagnoses for identifying probable causes for the deviation and the likelihood of each of the probable causes; comparing the diagnoses with the process model and updating the process model based on a diagnosis of high certainty if the cause for the deviation is the process model, and if sufficiently uncertain to differentiate a likely cause, initiating additional diagnoses; assessing opportunity and/or risk of control action based on the identified probable causes for the deviation and their likelihood; and recommending at least one control action to control the process based on said assessment. - View Dependent Claims (24, 25, 26, 27)
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9. A system for controlling a process of at least one device in response to data collected from a plurality of sensors, said system comprising:
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a status agent for monitoring the status of the system based on data collected from the sensors; at least one diagnostic agent for diagnosing at least a portion of the system and collecting diagnostic data from the sensors to identify deviation from normal operation; a control agent for performing control actions to the process; and a supervisory manager coupling to the status agent, the at least one diagnostic agent and the control agent for; receiving real time process data generated from the process; comparing against at least one of a predictive objective function, a historical mean, a predicted operational envelope and a predetermined static function of a process model of the process, for establishing any deviation from normal operation; classifying, at the status agent, a source of the deviation and likely cause of the deviation; prioritizing actuation of the at least one diagnostic agent related to causality of the deviation; modifying the process model based on the results of the at least one diagnostic agent, if the source of the deviation is the process model; and applying the process model at a control agent for evaluating risk and recommending appropriate control action to control the process of the at least one device. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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Specification