Distributed Control Latency Estimation for Adaptive Networked Systems
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Solution Overview
Problem
Existing control design methods in distributed systems lack precise knowledge of latency within the control loop, leading to potential instability and suboptimal performance due to unpredictable timing effects and variable communication delays.
Innovation Solution
A method for estimating latency in a network distributed system by determining sensor and actuator latencies, providing multiple control functions, applying a latency correction term, and selecting an appropriate control function based on the corrected total latency to ensure accurate control input application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If distributed control systems use network communication to connect control algorithm and physical plant, then system flexibility and scalability are improved, but latency prediction accuracy deteriorates due to unpredictable network delays
Solution Approach 1:
The system performs preliminary latency estimation before control execution by analyzing sensor time information and network conditions. Multiple control functions are pre-prepared with different latency assumptions, allowing the system to select the appropriate control function based on predicted latency conditions, thus improving both flexibility and prediction accuracy.
Solution Approach 2:
The control system dynamically adapts to varying network latency conditions by providing multiple control functions optimized for different latency scenarios. The system selects and executes the most appropriate control function based on real-time latency estimates, enabling the control algorithm to remain effective despite unpredictable network delays.
2Productivity
If control systems use shared computing platform resources with concurrent applications, then resource utilization efficiency is improved, but control latency predictability deteriorates due to resource contention
Solution Approach 1:
The system estimates control latency in advance by considering shared resource conditions and concurrent application loads. This preliminary estimation allows the control system to prepare appropriate control functions that account for expected resource contention, maintaining reliability while utilizing shared resources efficiently.
Solution Approach 2:
The system uses feedback from latency measurements and resource utilization monitoring to continuously refine latency estimates. By comparing actual control loop latencies with predictions, the system adapts its estimation model to accurately predict latency under varying resource contention conditions, ensuring reliable control despite shared platform resources.
3Reliability
If control systems rely on offline latency models for robust control design, then worst-case schedulability verification is improved, but real-time adaptability to variable workloads deteriorates
Solution Approach 1:
The system combines offline latency model preparation with online latency estimation. Multiple control functions are pre-designed for different latency scenarios based on worst-case analysis, but the actual selection is made online based on real-time latency estimates, achieving both worst-case verification and real-time adaptability.
Solution Approach 2:
The control system transitions from static offline latency models to dynamic online latency estimation. By continuously estimating latency based on current operating conditions and selecting appropriate pre-prepared control functions, the system maintains robustness while adapting to variable workloads in real-time.
4Adaptability or versatility
If control systems use feedback-scheduling to adapt task schedules, then response to deadline misses is improved, but applicability to distributed settings with communication delays deteriorates
Solution Approach 1:
The system performs preliminary latency estimation that specifically accounts for distributed system characteristics including network communication delays. By estimating sensor latency, actuator latency, and control latency separately and combining them, the system achieves accurate total latency prediction suitable for distributed settings, enabling effective feedback-scheduling adaptation.
Data Source
AI summary
A method for estimating latency in a network distributed system with at least one sensor, a control unit, and an actuator for actuating on a technical system includes (i) determining a sensor latency between the sensor and the control unit based on sensor time information, (ii) estimating an actuator latency between the control unit and the actuator, (iii) providing multiple control functions each concerning a different estimated total latency, wherein the estimated total latency includes the sensor latency, the actuator latency and a control latency, (iv) providing a latency correction term based on a comparison between the estimated total latency and a measured total latency, (v) calculating a corrected total latency by using (adding) the latency correction term, available at the time of the estimation, to the total latency, (vi) selecting and executing a control function from the multiple control functions for which the corrected total latency lies within a latency range of this control function and calculating a control input from the selected control function, (vii) transmitting the control input to the actuator via the network, and (viii) applying, by the actuator, the control input to the technical system.