Mass Flow Controller PID Coefficient Adjustment for Pressure Insensitivity
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Solution Overview
Problem
Conventional mass flow controllers have limitations in Pressure Insensitive (PI) performance due to PID coefficients being proportional to the flow rate set value, leading to suboptimal control during pressure changes, with differing coefficients required for rising and falling primary pressures.
Innovation Solution
A mass flow controller that adjusts its PID coefficients based on primary pressure, time change amount of primary pressure, and flow rate set value, using specific functions to determine optimal coefficients for stable operation, thereby minimizing pressure influence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If PID coefficients are made proportional to the flow rate set value, then the control system is simplified, but the PI performance is limited and cannot achieve optimal control during pressure changes
Solution Approach 1:
The patent applies dynamics by making the PID coefficients variable rather than fixed. The proportional coefficient, integral coefficient, and derivative coefficient are dynamically adjusted based on the primary pressure value and its time change amount. This allows the control system to adapt to changing pressure conditions in real-time, achieving optimal PI performance without requiring an overly complex multi-layer control architecture.
Solution Approach 2:
The patent implements parameter changes by modifying the PID coefficients based on pressure conditions. Specifically, the proportional coefficient is changed according to the primary pressure value, while the integral and derivative coefficients are adjusted based on both the primary pressure and its time change amount. This parameter adaptation resolves the contradiction by maintaining simple proportional scaling while achieving pressure-insensitive performance through dynamic coefficient adjustment.
2Device complexity
If the same PID coefficients are used for both rising and falling primary pressure, then the control logic is simplified, but optimal control cannot be achieved since different coefficients are needed for pressure rise and fall
Solution Approach 1:
The patent uses dynamics to differentiate between pressure rising and falling conditions. By detecting the time change amount of the primary pressure, the system dynamically selects appropriate PID coefficients for each condition. This allows optimal control for both rising and falling pressure without requiring complex separate control paths, as the same coefficient adjustment mechanism adapts automatically based on the pressure trend.
Solution Approach 2:
The patent applies parameter changes by adjusting PID coefficients according to the direction of pressure change. Different coefficient sets are prepared for pressure rise and pressure fall conditions, and the system switches between them based on the detected pressure trend. This resolves the contradiction by maintaining simple conditional logic while achieving high flow rate control precision through condition-specific parameter optimization.
3Device complexity
If PID coefficients are fixed regardless of pressure conditions, then the control system is simplest, but the system cannot adapt to pressure changes and loses PI performance
Solution Approach 1:
The patent implements dynamics by making PID coefficients adaptive to pressure conditions. The proportional coefficient responds to primary pressure changes, while the integral and derivative coefficients respond to both pressure changes and their rates of change. This dynamic adaptation enables the system to maintain optimal performance across varying pressure conditions without requiring complex predictive or multi-mode control strategies.
Solution Approach 2:
The patent applies feedback by continuously monitoring the primary pressure and its time change amount, then using this information to adjust the PID coefficients. This closed-loop adaptation ensures the system maintains pressure insensitivity and optimal PI performance across different operating conditions, resolving the contradiction between simplicity and adaptability through intelligent feedback-driven parameter adjustment.
Data Source
AI summary
To improve PI performance of a mass flow controller, the mass flow controller changes a proportional coefficient, an integral coefficient, and a derivative coefficient used for PID operation in a stable state based on at least two out of a primary pressure, a time change amount of the primary pressure, and a flow rate set value.