Missile Avoidance Vehicle Control With Selective Model Switching
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Solution Overview
Problem
Existing automated vehicle systems lack reliability in controlling vehicle functions, particularly in complex scenarios involving missile avoidance, due to the limitations of single control models and the inability to adapt to varying operating conditions.
Innovation Solution
A vehicle management system with multiple control models, each trained for different scenarios, selects the most appropriate model based on current operating conditions, ensuring reliable command generation through a missile avoidance management unit and monitoring unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single control model is used for automated vehicle control, then the system structure remains simple, but the reliability of control in complex scenarios such as missile avoidance deteriorates
Solution Approach 1:
The control system is segmented into multiple independent control models (first control model, second control model, etc.), each specialized for different operating scenarios. The missile avoidance management unit divides the control task by selecting appropriate models based on current conditions, thereby improving reliability without requiring a single overly complex model to handle all scenarios
Solution Approach 2:
The vehicle management system achieves multi-functionality through multiple control models that can each handle specific types of scenarios. The system universally addresses various operating conditions (normal operation, missile threat, countermeasure deployment) by having different control models available, with the management unit selecting the appropriate model for each situation
2Reliability
If multiple control models are used for different scenarios, then the reliability of control in complex scenarios improves, but the device complexity increases
Solution Approach 1:
The missile avoidance management unit acts as an intermediary between multiple control models and the vehicle control system. It manages the complexity by selecting appropriate control models based on current operating conditions, allowing multiple specialized models to work together without requiring direct integration of all their functions in a single complex unit
Solution Approach 2:
The control system dynamically adapts by selecting different control models based on real-time operating conditions. The missile avoidance management unit enables dynamic switching between control models as scenarios change (e.g., from normal operation to missile threat to countermeasure deployment), making the system flexible without permanent complex structure
3Adaptability or versatility
If control models are selectively activated based on operating conditions, then the adaptability to varying scenarios improves, but the system complexity increases
Solution Approach 1:
The system adapts to different operating conditions by changing which control model is active based on parameters such as threat level, vehicle state, and scenario type. The missile avoidance management unit monitors operating condition parameters and selects control models accordingly, enabling adaptability through parameter-based model selection rather than structural complexity
Data Source
AI summary
A vehicle management system includes a missile avoidance system that generates command for controlling at least one function of a vehicle. The missile avoidance system includes a maneuver control unit and a missile avoidance management unit. The maneuver control unit includes at least two control models. Each of the at least two control models generates the command for controlling the at least one function of the vehicle, and each of the at least two control models can be selectively put in an active state or an inactive state. The missile avoidance management unit selects one of the at least two control models and putts it in the active state. The maneuver control unit outputs the command for controlling the at least one function of the vehicle provided by the control model that is in the active state.