Synchronized Flight Control Pipeline for Deterministic Actuation
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Solution Overview
Problem
Existing flight controller systems face challenges in efficiently processing sensor data and generating control signals due to asynchronous data polling and actuation, which can lead to performance issues and latency in real-time operations.
Innovation Solution
A pipeline-based flight controller system is introduced, where modules execute in parallel or sequence, with a scheduler managing execution times to prioritize tasks and ensure preemption, allowing for synchronous data processing and actuation, reducing latency and jitter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If asynchronous polling is used to read sensor data and write to actuators, then the system can operate with simple timing, but latency and performance issues occur in real-time operations
Solution Approach 1:
The controller is divided into multiple independent modules organized in a pipeline architecture, where each module handles specific tasks (sensor reading, data processing, actuator control). This segmentation allows parallel execution of modules, reducing overall latency while maintaining manageable timing complexity through modular design.
Solution Approach 2:
High-priority modules are scheduled to execute before lower-priority modules in the pipeline. This preliminary action ensures that time-critical operations (such as sensor data acquisition and safety-related actuator control) are completed with minimal latency, while less urgent tasks follow in sequence.
2Ease of manufacture
If modules execute asynchronously, then the system is easier to implement, but deterministic real-time performance cannot be guaranteed
Solution Approach 1:
The system implements a dynamic scheduling mechanism where module execution order and timing are adaptively determined based on priority levels. High-priority modules are dynamically scheduled to execute earlier in the pipeline, while lower-priority modules execute subsequently. This dynamic approach guarantees deterministic performance for critical tasks while maintaining implementation simplicity through a standardized pipeline framework.
3Speed
If high-priority tasks are executed frequently, then real-time responsiveness is improved, but lower-priority tasks may be starved of execution time
Solution Approach 1:
The pipeline allocates a portion of execution cycles to high-priority modules to ensure rapid response, while guaranteeing that lower-priority modules receive sufficient execution time to complete their tasks. This partial action approach prevents complete starvation of lower-priority tasks while maintaining high responsiveness for critical operations.
Solution Approach 2:
The system implements periodic execution of modules in the pipeline, where each module is guaranteed a regular execution slot. This periodic scheduling ensures that both high-priority and lower-priority tasks receive consistent execution opportunities, preventing starvation while maintaining predictable response times for real-time operations.
Data Source
AI summary
A pipeline in a controller may be configured to interface between sensors and actuators. The pipeline may include elements such as drivers, filters, a combine, estimators, controllers, a mixer, and actuator controllers. The drivers may receive sensor data and pre-process the received sensor data. The filters may filter the pre-processed sensor data to generate filtered sensor data. The combine may package the filtered sensor data to generate packaged sensor data. The estimators may determine estimates of a position of a vehicle based on the packaged sensor data. The controllers may generate control signals based on the determined estimates. The mixer may modify the generated control signals based on limitations of the vehicle. The actuator controllers may generate actuator control signals based on the modified control signals to drive the actuators.