Process Robustness Testing for Missing Control Inputs
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Solution Overview
Problem
Latency in networked control systems can destabilize and degrade the performance of control loops due to varying delays between the controller and the controlled system.
Innovation Solution
A method and device for testing a process by determining successive values of state variables without control input until a quadratic Lyapunov function reaches a threshold, assessing robustness, and using control input to guide the process, with a computer program executing the method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If networked control is used to enable remote control via communication network, then control flexibility and remote operation capability are improved, but latency and instability in control loop are introduced
Solution Approach 1:
The system performs preliminary actions by predicting future process states and proactively adjusting control inputs before latency effects manifest. The prediction mechanism calculates anticipated state variables and pre-computes control inputs that will maintain stability despite upcoming communication delays.
Solution Approach 2:
The control system dynamically adapts its behavior based on current process conditions and estimated latency. The prediction horizon and control strategy are adjusted in real-time according to the actual state of the process and network conditions, making the system flexible and responsive to changing conditions.
2Reliability
If latency compensation methods are implemented to improve control stability, then control loop reliability is improved, but computational complexity and processing requirements increase
Solution Approach 1:
The system changes key parameters such as the prediction horizon length and control input adjustment magnitude based on the actual process conditions and observed latency patterns. By dynamically adjusting these parameters, the system achieves effective latency compensation without requiring excessively complex computational models.
Solution Approach 2:
The system creates a simplified predictive model that copies the essential dynamics of the process behavior. This predictive copy allows the controller to anticipate future states and compute appropriate control actions without requiring full complexity of the actual process model, reducing computational burden while maintaining effectiveness.
Data Source
AI summary
A device and a method for testing a process. A state variable of the process is controllable using a control input from a controller. The method includes determining successive values of the state variables without control input, starting from an initial value of the state variables, and a set of the successive values of the state variables, which can be calculated, until the quadratic Lyapunov function for the value of the state variables reaches a predetermined threshold value, and determining that the process is robust with respect to the set of successive values without control input.