Critical environment feedforward-feedback control system with room pressure and temperature control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional control systems struggle to accurately and consistently maintain temperature and pressure within controlled spaces, particularly in environments like laboratories or hospitals, due to the thermodynamic relationship between these variables and the impact of disturbances such as fume hood operations.
Innovation Solution
A feedforward-feedback controller that integrates temperature and pressure control, using processing circuits to generate supply air flow and temperature setpoints, proactively compensating for disturbances and reactively adjusting to errors, ensuring equipment capabilities are met, and optimizing airflow to maintain desired conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional control systems are used to maintain temperature and pressure in controlled spaces, then the system structure is simple, but the system cannot accurately and consistently maintain temperature and pressure within tight tolerances
Solution Approach 1:
The control system is segmented into distinct functional modules: a feedforward control module that proactively responds to known disturbances (e.g., fume hood operations), a feedback control module that reactively corrects deviations from setpoints, and a predictive temperature model. This modular segmentation allows each component to specialize in specific control tasks, achieving high precision temperature and pressure control while maintaining manageable system complexity through organized functionality.
Solution Approach 2:
The feedforward control component implements preliminary action by proactively detecting anticipated disturbances (such as scheduled fume hood operations) and applying compensatory control actions before the disturbances actually affect the controlled space. This predictive compensation prevents temperature and pressure deviations before they occur, significantly improving control precision without requiring overly complex reactive systems.
2Stability of the object's composition
If control systems actively respond to disturbances, then temperature and pressure stability improves, but computational resources and software adjustments increase
Solution Approach 1:
The control system applies partial action by focusing computational efforts only on the most significant disturbances and control variables. The feedforward control targets specific known disturbances (e.g., fume hood operations) rather than attempting to compensate for all possible variations. The predictive temperature model uses simplified thermodynamic relationships to generate adequate control actions without requiring exhaustive computational analysis, achieving acceptable stability while conserving computational resources.
3Reliability
If feedforward and feedback control are both implemented, then disturbance compensation improves, but device complexity increases
Solution Approach 1:
The feedforward and feedback control components are merged into a unified control architecture that shares common elements such as the predictive temperature model, setpoint management, and actuator control. The feedforward path handles known disturbances proactively, while the feedback path corrects residual deviations, and both paths converge on the same control outputs. This merging reduces redundancy and integrates the two control strategies into a cohesive system, improving disturbance compensation while preventing excessive complexity through shared functionality.
Data Source
AI summary
A feedforward-feedback controller for integrated temperature and pressure control of a building space includes one or more processing circuits. The one or more processing circuits are configured to generate a supply air flow rate setpoint using a combined feedforward-feedback control process that (i) proactively compensates for a feedforward air flow disturbance in the building space and (ii) reactively compensates for a feedback air pressure error in the building space, generate a supply air temperature setpoint using a predictive temperature model that predicts the supply air temperature setpoint required to achieve a zone temperature setpoint for the building space when supply air is provided to the building space at the supply air flow rate setpoint and the supply air temperature setpoint, and operate building equipment to provide the supply air to the building space at the supply air flow rate setpoint and the supply air temperature setpoint.