Normalized Setpoint Alarming for HVAC Feedback Control Loops
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Solution Overview
Problem
Traditional methods for calculating performance indices of feedback controllers in HVAC systems are difficult to evaluate and compare across systems, as they depend on specific system parameters and are computationally expensive, limiting their application to offline batch analysis.
Innovation Solution
A feedback control system that uses exponentially-weighted moving average (EWMA) statistics to generate normalized performance indices, allowing for real-time monitoring and setpoint alarming without requiring knowledge of specific system parameters, using alarm parameters κ and η to set thresholds independently of system variables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional performance measures are used to quantify feedback controller performance, then the measures reflect system-specific characteristics, but the measures become difficult to evaluate and compare across different systems
Solution Approach 1:
The patent transforms traditional performance measures by normalizing them using system-specific parameters such as ultimate gain, ultimate period, and area under the curve. This normalization converts absolute performance values into dimensionless normalized indices that can be compared across different systems while preserving the underlying performance characteristics.
2Measurement precision
If traditional normalized index calculation methods are used, then the indices enable cross-system comparison, but the calculation becomes computationally expensive
Solution Approach 1:
The patent pre-calculates and stores the ultimate gain, ultimate period, and area under the curve parameters during system commissioning or initial operation. These pre-computed parameters are then reused for ongoing performance monitoring, avoiding repeated computationally expensive calculations while maintaining normalized index accuracy.
Solution Approach 2:
The patent implements a hybrid approach where static system parameters (ultimate gain, period) are determined offline, while dynamic performance metrics (area under the curve, normalized indices) are calculated online using simplified recursive algorithms that update incrementally with each new data point.
3Measurement precision
If traditional batch analysis methods are used for performance evaluation, then comprehensive data analysis is possible, but real-time monitoring and alarm generation are not enabled
Solution Approach 1:
The patent implements continuous performance monitoring by calculating normalized indices recursively at each control cycle using the most recent area under the curve values. This continuous calculation enables real-time performance tracking and immediate alarm generation when performance thresholds are violated, eliminating the time delay inherent in batch processing methods.
Data Source
AI summary
A setpoint alarming system includes a feedback controller that monitors a process variable provided as a feedback signal from a plant and uses an error signal representing a difference between the process variable and a setpoint to generate a control signal for the plant. The plant uses the control signal to affect the process variable. The system includes a normalized index generator that uses the error signal to generate a normalized performance index for the plant. The system includes an expected value estimator that estimates a value of the normalized performance index expected to occur when a setpoint error of a predetermined magnitude has persisted for a predetermined duration. The system includes an alarm manager that compares the normalized performance index to the expected value and generates an alarm in response to the normalized performance index dropping below the expected value.