Real-Time Control Using Parallel Optimization Consistency Checks
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Solution Overview
Problem
Existing optimization-assisted automatic control techniques for electric vehicles face challenges due to unreliable solutions produced by numerical optimization solvers, which can lead to erroneous control signals and safety concerns, especially in critical control strategies where timely and reliable control is essential.
Innovation Solution
A method that involves sensing the state of a technical system and initiating independent executions of multiple optimization processes to solve an optimal-control problem. After a predetermined delay, the method extracts solution vectors from each process, computes differences between them, and selects the most reliable solution vector for controlling the system, thereby reducing the failure rate of control signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple optimization processes are executed in parallel to improve reliability, then the failure rate of control signals is reduced, but the computational complexity and processing time increase
Solution Approach 1:
The control system is segmented into multiple independent optimization processes (P1, P2, P3, ...) that operate in parallel. Each process independently solves the optimization problem and generates a solution vector, allowing the system to divide the computational task into manageable segments that can be processed simultaneously, thereby improving reliability without overwhelming a single processor
Solution Approach 2:
The results from multiple independent optimization processes are merged through a selection mechanism. The controller compares solution vectors from different processes and selects the most reliable one based on convergence criteria and consistency checks, effectively combining the outputs to achieve higher overall reliability while maintaining real-time performance
2Measurement precision
If iterative optimization methods are used to solve the optimal control problem, then the control accuracy is improved, but the convergence time becomes unpredictable and may exceed the scheduled time
Solution Approach 1:
The system performs preliminary actions by initializing multiple optimization processes simultaneously at the beginning of each control cycle. Each process starts with pre-configured parameters and convergence criteria, allowing them to work independently toward a solution within the scheduled time frame, rather than sequentially or with unpredictable delays
Solution Approach 2:
A feedback mechanism monitors the convergence status of each optimization process in real-time. The controller continuously checks whether solution vectors meet convergence criteria and selects the best solution based on this feedback, allowing the system to adapt to varying convergence speeds while ensuring timely completion within the scheduled time
3Productivity
If a single optimization process is used to reduce computational complexity, then the processing speed is maintained, but the reliability of control signals decreases due to potential convergence failures
Solution Approach 1:
Different optimization processes are assigned different local qualities or characteristics, such as varying initial conditions, different algorithm parameters, or distinct search strategies. This diversity in local approaches increases the likelihood that at least one process will converge successfully, thereby improving reliability while maintaining overall processing speed through parallel execution
Data Source
AI summary
A method for controlling a technical system in real time, comprising: sensing a state of the technical system; with the sensed state, initiating independent executions of a plurality of optimization processes (P1, P2, P3, . . . ) configured to solve a predefined optimization problem related to optimal control of the technical system; after a predetermined delay, extracting a current solution vector (u1, u2, u3, . . . ) from each optimization process; computing differences (dij˜∥ui−uj∥) for pairs of the solution vectors; and on the basis of the differences, selecting at least one of the solution vectors for use in controlling the technical system.