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US 2015/0148919 A1Published application
Method and apparatus for artificially intelligent model-based control of dynamic processes using probabilistic agents
AssigneeAdept Ai Systems Inc.
InventorJeff WATSON
Life of this patent
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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.
Claims9
A method for controlling a process comprising:
- receiving real time process data generated from the process;
- comparing against a predictive objective function and/or a historical mean and/or a predicted operational envelope and/or a predetermined static function for establishing any deviation from normal operation;
- applying probabilistic modeling at a status agent for classifying the source and likely cause of the deviation;
- prioritizing actuation of at least one or more diagnostic agents related to causality of the deviation at a supervisory manager;
- communicating the results of the diagnostic agents to the supervisory manager;
- modifying the probabilistic model of the status agent from the results from the one or more diagnostic agents;
- and
- applying a probabilistic model at a control agent for evaluating risk and recommending and initiating an appropriate control action to the process.
5 more elements
A method of controlling a process comprising:
- comparing real time data to statistical and/or historical profiles of the process or a simulated profile of the process, taking into account operational variance and thereby identifying deviations;
- tracking the progress and the specific states of the process at a status agent and classifying probable diagnostic agents relevant to the deviations;
- and under the management of an AI Manager,
- triggering the appropriate diagnostic agents with causal process-specific PGNs for identifying probable causes for the deviation and their likelihood, and receiving the probabilistic diagnoses;
- comparing the probabilistic diagnoses of the various diagnostic agents and updating the Status Agent of the diagnosis of high certainty, or if sufficiently uncertain to differentiate a likely cause, initiating additional tests;
- and
- assessing opportunity and/or risk of control action at a control agent based on the probability of one or more diagnoses and recommending a control action to the process based on the opportunity/risk analysis.
4 more elements
A system for controlling a process in response to data collected from a plurality of sensors, said system comprising:
- 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 a predictive objective function and/or a historical mean and/or a predicted operational envelope and/or a predetermined static function for establishing any deviation from normal operation;
- applying probabilistic modeling at the status agent for classifying the source and likely cause of the deviation;
- prioritizing actuation of the at least one diagnostic agent related to causality of the deviation;
- modifying the probabilistic model of the status agent from the results from the at least one diagnostic agent;
- and
- applying a probabilistic model at a control agent for evaluating risk and recommending appropriate control action to the process.
9 more elements
Dependencies are inferred from the claim text.