Virtual Control Engine for Dynamic Logic Execution
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Solution Overview
Problem
Existing control systems for industrial equipment are complex and costly to maintain due to the need for frequent shutdowns during changes in control logic, often resulting in discrepancies between intended and implemented logic, especially when handling sensor and actuator faults or environmental changes.
Innovation Solution
The implementation of a virtual control engine that uses attributed data to dynamically execute control logic, allowing for quick updates and consistent deployment across multiple hardware platforms without the need for new software, enabling continuous operation and reducing development and maintenance costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If control logic is changed to handle sensor and actuator faults or environmental changes, then system reliability is improved, but device complexity increases due to highly complex control software
Solution Approach 1:
The patent segments control logic into modular control blocks that can be independently selected and configured. Each control block handles specific control functions, allowing the system to compose complex control behavior from simpler, reusable modules. This reduces overall system complexity while maintaining reliability through targeted fault handling capabilities.
Solution Approach 2:
The system dynamically changes control parameters and logic based on detected fault conditions or environmental changes. Instead of hardcoding multiple alternative control paths, the system adapts existing control logic by modifying parameters in response to sensor and actuator fault detections, thereby improving reliability without proportionally increasing complexity.
2Reliability
If alternative control logic is included for fault handling, then system reliability is improved, but ease of operation deteriorates due to frequent shutdowns required for software updates
Solution Approach 1:
The control logic is implemented as dynamic, reconfigurable software that can be updated without system shutdown. The modular control blocks can be loaded, modified, and activated while the system operates, enabling continuous fault handling capability updates without sacrificing system availability or ease of operation.
Solution Approach 2:
Multiple alternative control logic blocks are pre-configured and stored in the system memory for various fault conditions. When a fault is detected, the system immediately switches to the appropriate pre-prepared control logic without requiring shutdown or real-time compilation, thereby maintaining high availability while providing robust fault handling.
3Adaptability or versatility
If control logic is re-designed for new conditions, then adaptability is improved, but loss of time increases due to system shutdowns during deployment
Solution Approach 1:
The system employs dynamic loading and activation of control logic blocks. New control logic can be uploaded and activated during system operation, allowing the system to adapt to new conditions or fault patterns without shutdown. This dramatically reduces the time loss associated with deploying updated control software while maintaining high adaptability.
4Reliability
If comprehensive control logic is implemented to handle all predictable faults, then reliability is improved, but device complexity increases resulting in costly maintenance
Solution Approach 1:
The control system is divided into independent, parameterized control blocks that can be selectively activated based on detected faults. This segmentation allows the system to maintain comprehensive fault coverage by enabling only the necessary control blocks for current operating conditions, thereby reducing the effective complexity and maintenance burden compared to having all control logic permanently embedded and active.
Data Source
AI summary
Disclosed herein, in various embodiments, are systems and methods for creating, implementing, communicating, and/or analyzing control logic governing operation of a system under control, where the control logic is defined in attributed data, which specifies control operators along with their input and output variables for the various control nodes. In example embodiments, a virtual control engine executes the control logic based on interpretations provided by an attributed-data dictionary.