Pareto Front Reuse in Multi-Objective Real-Time Control
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Solution Overview
Problem
Current methods for real-time control of dynamic systems with multiple objectives require frequent re-determination of the Pareto front, leading to high computational workload, resource usage, and time consumption, making them unsuitable for efficient control in real-time scenarios.
Innovation Solution
A computer-implemented method that uses past Pareto fronts to compute control inputs for current time steps, reducing the need for repeated computation by estimating similarity between new and past Pareto fronts, allowing for the reuse of previously computed solutions when conditions remain similar.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the Pareto front is re-determined at every time step for dynamic systems, then the control optimality according to multiple objectives is improved, but the computational workload and time consumption increase significantly
Solution Approach 1:
The patent pre-computes and stores the Pareto front in advance before real-time control execution. This preliminary action allows the stored Pareto front to be directly applied during real-time control without repeated computation, resolving the contradiction between maintaining control optimality and reducing computational time burden
Solution Approach 2:
The patent creates a copy of the pre-computed Pareto front and stores it for reuse. Instead of re-determining the Pareto front at every time step, the system copies and applies the stored Pareto front to current control problems, significantly reducing computational workload while maintaining solution quality
2Extent of automation
If simple mathematical metrics are used to automatically select a Pareto optimal solution, then the automation level is improved, but the computational resources and workload increase
Solution Approach 1:
The patent employs a learning module that automatically learns user preferences from historical selection data. This self-service mechanism enables the system to automatically select Pareto optimal solutions based on learned preferences without requiring complex real-time computation or manual user input, thus achieving automation while controlling computational resource usage
Data Source
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AI summary
The present invention provides a computer-implemented method for repeatedly computing a control input for a control of a system according to objectives. The method comprises computing, at a current time step, the control input according to the objectives using one or more Pareto fronts that were generated for computing, at one or more respective time steps before the current time step, the control input according to the objectives. The present invention further provides a data processing apparatus comprising means for carrying out the aforementioned method; a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the aforementioned method; and a computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the aforementioned method.