For equal-percent valves, which approach helps address nonlinearity in a control loop?

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Multiple Choice

For equal-percent valves, which approach helps address nonlinearity in a control loop?

Explanation:
Nonlinearity in equal-percent valves comes from the valve’s opening-to-flow relationship, which makes the plant gain vary as the valve position changes. Because the valve doesn’t respond linearly, a fixed controller gain can overperform in one region and underperform in another, leading to uneven tracking and possible instability. The way to handle this is to either schedule the controller gains based on the operating point (gain scheduling) or to use a nonlinearity compensator that accounts for the valve’s actual characteristic. Gain scheduling uses different linear controllers or gains for different ranges of valve position (or flow) and interpolates between them as the operation shifts, effectively linearizing the overall behavior across the range. Nonlinearity compensation—such as a model-based precursor that maps the desired flow through the inverse valve characteristic—can linearize the loop response by canceling part of the nonlinearity before the controller acts. These approaches explicitly address the changing plant gain, improving accuracy and stability across the operating range. In contrast, simply increasing proportional gain ignores the changing dynamics and can destabilize the loop in regions with higher or lower valve gain, removing feedback undermines regulation, and on/off control is too coarse to manage the nuanced nonlinear response.

Nonlinearity in equal-percent valves comes from the valve’s opening-to-flow relationship, which makes the plant gain vary as the valve position changes. Because the valve doesn’t respond linearly, a fixed controller gain can overperform in one region and underperform in another, leading to uneven tracking and possible instability. The way to handle this is to either schedule the controller gains based on the operating point (gain scheduling) or to use a nonlinearity compensator that accounts for the valve’s actual characteristic. Gain scheduling uses different linear controllers or gains for different ranges of valve position (or flow) and interpolates between them as the operation shifts, effectively linearizing the overall behavior across the range. Nonlinearity compensation—such as a model-based precursor that maps the desired flow through the inverse valve characteristic—can linearize the loop response by canceling part of the nonlinearity before the controller acts. These approaches explicitly address the changing plant gain, improving accuracy and stability across the operating range. In contrast, simply increasing proportional gain ignores the changing dynamics and can destabilize the loop in regions with higher or lower valve gain, removing feedback undermines regulation, and on/off control is too coarse to manage the nuanced nonlinear response.

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