Automated Plant Control With Redundant Multivariable Controllers
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Solution Overview
Problem
Industrial plant operations, particularly nuclear power plants, require continuous human operator intervention for desired operations and lack a facility-wide automated controller to coordinate component-level data and automate facility-wide changes, leading to potential unproductive or dangerous conditions.
Innovation Solution
An automated instrumentation and control system featuring multivariable controllers that interface with plant sensors and actuators, perform calculations based on physics models, and issue control commands without human intervention, ensuring redundancy and reliability even in the event of component failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators continuously monitor and control plant operations, then operational safety and responsiveness are maintained, but operator workload and potential for human error increase
Solution Approach 1:
The control system performs self-diagnosis and self-correction by automatically detecting component failures, voting on redundant signals, and executing predetermined control sequences without operator intervention. The system monitors its own state and takes corrective actions, freeing operators from continuous monitoring while maintaining safety through automated reliability mechanisms.
Solution Approach 2:
The system continuously receives feedback from sensors monitoring plant parameters and component status, processes this information through redundant controllers, and automatically adjusts operations based on the feedback. This closed-loop feedback enables the system to maintain safe operations autonomously by responding to changing conditions without operator input.
2Productivity
If automated control systems are implemented to reduce human intervention, then operational efficiency improves, but system complexity increases
Solution Approach 1:
The control system is divided into multiple independent modular controllers that each manage specific functions. Each controller operates independently with its own sensors and actuators, allowing the system to achieve automation through coordinated modular units rather than a single complex system. This segmentation reduces overall system complexity while maintaining high operational efficiency.
Solution Approach 2:
The redundant controllers are designed with universal functionality to perform multiple control functions through software configuration rather than dedicated hardware for each function. This multi-functionality allows the same physical controllers to handle various plant operations, reducing hardware complexity while enabling comprehensive automated control across different operational modes.
3Reliability
If redundant controllers are used to ensure continued operation during failures, then system reliability improves, but device complexity and cost increase
Solution Approach 1:
The system uses identical copies of the same controller hardware and software logic arranged in a redundant configuration. Each controller is a duplicate capable of independent operation, and the redundancy is achieved through configuration rather than specialized components. This copying approach ensures continued operation during failures while minimizing the complexity increase compared to using different or specialized redundant components.
Solution Approach 2:
The system achieves redundancy through changes in the operational parameters and configuration states of the controllers rather than through additional specialized hardware. By configuring controllers to operate in redundant modes and using voting logic to select between controller outputs, the system achieves high reliability without proportionally increasing device complexity.
Data Source
AI summary
Systems and methods provide data gathering and execution on the same without human operations. Systems may include controls and sensors that electronically provide data and operations to a processor networked with the same. For a nuclear reactor, the processor may determine reactivity from the sensors and issue commands to actuators to operate the reactor. Reactivity may be determined based on all reactivity factors determined from the plant data, including the use of modelling. The processor may position control elements or moderator feeds to achieve a desired reactivity. The processor may be networked to plant switches and sensors, and multiple processors may be used to independently calculate and decide on plant operations. Human operator input is not required at discreet instances of plant operational change; systems may include displays and input interfaces to permit observation and/or intervention if absolutely necessary.