Flight Control Verification for Octorotor Rotor Failure Safety
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Solution Overview
Problem
Multirotor aerial vehicles, such as octorotors, face instability and loss of control due to rotor failures, and existing solutions for fault-tolerant control are costly, require manual oversight, and lack flexibility in adapting to new environments or unplanned processes.
Innovation Solution
A computerized method and system using barrier functions and satisfiability modulo theories (SMT) solvers to evaluate and verify the safety of flight controls, identifying invariant sets and ensuring accurate command tracking even with rotor failures, by defining a vehicle dynamics model and constructing barrier functions to analyze and confirm control commands within safe regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If rules-based or expert knowledge systems are used for control, then flight safety can be maintained, but the system requires manual oversight and has limited flexibility in new environments
Solution Approach 1:
The system performs self-verification of control commands using barrier functions and SMT solvers. The autonomous subsystem automatically checks whether control commands satisfy safety specifications without requiring manual oversight, enabling the system to adapt to new environments while maintaining safety through automated formal verification methods
Solution Approach 2:
The patent replaces traditional rules-based control systems with a formal verification approach using barrier functions and satisfiability modulo theories (SMT) solvers. This substitution transforms the safety assurance mechanism from manual rule-checking to automated mathematical verification, improving both adaptability and efficiency
2Extent of automation
If autonomous subsystems are used with rules-based systems, then some automation is achieved, but manual oversight is still required and flexibility remains limited
Solution Approach 1:
The patent merges the control synthesis and safety verification into a unified framework. Barrier functions are constructed to encode safety specifications directly within the control system, and SMT solvers automatically verify both control performance and safety properties simultaneously, eliminating the need for separate manual oversight layers while managing complexity through integration
3Reliability
If existing fault-tolerant control solutions are implemented, then rotor failure resilience is improved, but the systems are costly and require extensive manual oversight
Solution Approach 1:
The system uses computationally efficient barrier functions that can be quickly synthesized and verified using SMT solvers. This approach replaces costly, complex fault-tolerant control implementations with more economical automated verification methods that provide equivalent or superior safety guarantees at lower implementation costs
Solution Approach 2:
The barrier functions are constructed beforehand to encode safety specifications for potential rotor failures. By pre-defining these safety barriers and using automated SMT verification, the system prepares for fault scenarios without requiring expensive real-time manual intervention or complex adaptive algorithms during actual failure events
Data Source
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AI summary
Systems and methods provide for the evaluation of flight controls for an aerial vehicle and define a vehicle dynamics model corresponding to an aerial vehicle. One or more barrier functions are constructed based on the defined vehicle dynamics model, and candidate invariant sets are identified for the defined vehicle dynamics model using the one or more barrier functions. A plurality of flight controls of the aerial vehicle are analyzed using the identified candidate invariant sets and within the analyzed candidate invariant sets, command tracking of the aerial vehicle is confirmed with control commands, using the analyzed plurality of flight controls. Control commands falling outside of the analyzed candidate invariant sets are identified.