Online Optimal Control With Buffer Constraints for Safety Policies
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Solution Overview
Problem
Current control systems are too restrictive and fail to adapt to time-varying environments, lacking optimal performance due to the inability to handle system disturbances and time-invariant environments, leading to suboptimal safety algorithms that sacrifice performance for safety.
Innovation Solution
The method converts constrained online optimal control problems into Online Convex Optimization (OCO) with temporal-coupled stage costs and constraints, introduces buffer zones to account for approximation errors, and applies classical OCO algorithms like Online Gradient Descent (OGD) to generate optimal safety policies that minimize adversarial varying costs while satisfying constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current control systems use fixed safety algorithms, then constraint satisfaction is improved, but adaptability to time-varying environments deteriorates
Solution Approach 1:
The patent transforms static safety algorithms into dynamic online optimization algorithms that continuously adapt to time-varying environments. The OCO framework allows the control system to dynamically adjust its behavior based on changing conditions while maintaining constraint satisfaction through buffer zones and theoretical guarantees.
2Reliability
If control systems apply restrictive safety constraints, then safety is improved, but performance deteriorates
Solution Approach 1:
The patent changes the parameters of safety constraints by introducing buffer zones that are dynamically adjusted based on system state and disturbance levels. This allows the system to maintain safety guarantees while reducing the restrictiveness of constraints, thereby improving performance.
Solution Approach 2:
The patent applies partial constraint satisfaction through buffer zones, where constraints are satisfied to the extent necessary for safety while allowing flexibility for optimal performance. The buffer zone mechanism provides exactly enough constraint to ensure safety without excessive restriction.
3Adaptability or versatility
If control systems use online optimization algorithms, then adaptability to time-varying environments is improved, but handling of system disturbances deteriorates
Solution Approach 1:
The patent prepares for future disturbances by introducing buffer zones in advance of actual constraint violations. These buffer zones act as a cushion that absorbs the impact of system disturbances, allowing the online optimization algorithm to adapt to time-varying environments while maintaining reliability during disturbances.
Data Source
AI summary
Embodiments of the present invention provide computer-implemented methods, computer program products and computer systems. Embodiments of the present invention can identify a plurality of constraints on states of data and actions of data associated with a data model. Embodiments of the present invention can then identify constraints on safety policy parameters associated with a computing device. Embodiments of the present invention can then convert the identified constraints into a uniform domain syntax that considers coupled and decoupled constraints and introduce buffer data within the converted constraints, wherein the buffer data filters outlier constraints within the plurality of constraints. Embodiments of the present invention can then dynamically generate optimal safety policies associated with the computing device based on the remaining constraints.