Adaptive Sampling Rate Control for Dynamic Plant Stability
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Solution Overview
Problem
Determining an appropriate sampling rate for feedback controllers is challenging, as a rate that is too fast can lead to improper tuning of proportional gain, while a rate that is too slow can result in poor performance, especially in dynamic systems affected by external conditions.
Innovation Solution
A control system that estimates the response time of a plant and adjusts the sampling rate based on this estimation, using methods such as integrating error signals or determining time constants to set an optimal sampling rate, thereby improving the adaptive feedback controller's performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the sampling rate is increased to improve control responsiveness, then the control performance is improved, but the proportional gain becomes too small and tuning becomes improper
Solution Approach 1:
The patent implements adaptive tuning algorithms that dynamically adjust control parameters including sampling rate based on observed system behavior. The controller transitions from static parameter settings to dynamic adaptation, automatically modifying the sampling rate to match changing process conditions and maintain optimal proportional gain values.
Solution Approach 2:
The system uses feedback from observed system response to continuously monitor and adjust the sampling rate. By measuring the actual system behavior and comparing it against desired performance criteria, the controller automatically modifies the sampling rate to prevent improper tuning while maintaining responsiveness.
2Device complexity
If the sampling rate is decreased to reduce computational load, then the system complexity is reduced, but the control performance suffers
Solution Approach 1:
The controller dynamically adjusts the sampling rate based on process conditions rather than using a fixed rate. During stable operating conditions, the sampling rate is reduced to lower computational load. During transient or disturbed conditions, the sampling rate increases automatically to maintain control performance, achieving both goals adaptively.
3Manufacturing precision
If manual adjustment of sampling rate is implemented to optimize control parameters, then the manufacturing precision is improved, but the ease of operation deteriorates
Solution Approach 1:
The control system performs self-tuning by automatically adjusting its own sampling rate and control parameters based on observed system behavior. The adaptive tuning algorithm enables the controller to optimize its performance without external intervention, eliminating the need for manual parameter adjustment while maintaining high precision control.
Data Source
AI summary
A control system for a plant includes a controller and a sensor. The controller is configured to estimate a response time of the plant and adjust a sampling rate based on the estimated response time. The response time is a parameter that characterizes a response of the plant to a disturbance. The sensor is configured to receive the adjusted sampling rate from the controller, collect samples of a measured variable from the plant at the adjusted sampling rate, and provide the samples of the measured variable to the controller.