Rate-Based Multivariable Control Stability Assurance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Multivariable control methods in process industries face challenges due to inaccurate models and aggressive control strategies, leading to instability and inefficiency, with existing model-based approaches being unreliable and prone to oscillations as process gains change dynamically.
Innovation Solution
A rate-based multivariable control method that uses direct control variables to control indirect variables, determining necessary control moves based on pre-selected move sizes and rate-of-change calculations, with stability assurance mechanisms to halt moves during instability, allowing for gradual and stable process optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If model-based predictive control is used to achieve automated multivariable constraint control and optimization, then productivity and operational efficiency are improved, but reliability deteriorates due to model inaccuracy and process gain changes
Solution Approach 1:
The patent transitions from model-based control parameters to a rate-based control approach that uses pre-selected move sizes and rate-of-change calculations. This changes the fundamental control parameters from model-predicted values to empirically-determined rate limits, making the control system adaptive to actual process behavior rather than relying on potentially inaccurate models.
Solution Approach 2:
The control system uses the process's own rate-of-change characteristics to self-regulate control moves. By calculating the actual rate of change of controlled variables and using this information to limit subsequent moves, the system adapts to changing process conditions without requiring external model updates or manual intervention.
2Productivity
If aggressive model-based control strategies are implemented to reach target values quickly, then productivity is improved, but stability deteriorates due to oscillations and instability
Solution Approach 1:
The patent applies partial action by using pre-selected move sizes that are intentionally conservative rather than maximizing the control move magnitude. The rate-of-change calculations further limit the control action to what is necessary to progress toward the target without overshooting, achieving a balance between response speed and stability.
Solution Approach 2:
The control system incorporates beforehand cushioning by using stability assurance mechanisms that predict potential instability conditions and halt control moves in advance. The rate-based approach inherently cushions aggressive control actions by limiting move sizes based on observed process rates, preventing oscillations before they occur.
3Reliability
If manual multivariable control is used to ensure process stability and safety, then reliability is improved, but productivity deteriorates due to conservative operation away from constraints
Solution Approach 1:
The patent implements feedback by continuously monitoring the rate of change of controlled variables and using this information to adjust control moves. The system feeds back actual process behavior (rate-of-change) to modify future control actions, enabling automated control that adapts to changing conditions while maintaining stability.
Solution Approach 2:
The control system transitions from static manual control to dynamic automated control that adapts to changing process conditions. The rate-based approach with pre-selected move sizes allows the system to dynamically adjust control aggressiveness based on actual process response, enabling operation closer to constraints while maintaining stability.
4Adaptability or versatility
If model-based control adapts to changing process gains, then adaptability is improved, but complexity increases due to model updates and recalibration
Solution Approach 1:
The control system uses the process's own rate-of-change characteristics to self-regulate control moves. By calculating the actual rate of change of controlled variables and using this information to limit subsequent moves, the system adapts to changing process conditions without requiring external model updates or manual intervention.
Solution Approach 2:
The patent replaces the mechanical complexity of model-based control with a simpler rate-based computational approach. Instead of using complex mathematical models to predict process behavior, the system directly measures and uses the actual rate of change, substituting empirical observation for theoretical modeling.
Data Source
AI summary
Method, system and computer executable instructions for controlling a process.