Correlation-Based Control for MIMO Engine Stability
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Solution Overview
Problem
Conventional control apparatuses face stability and accuracy issues when controlling objects with extremal characteristics or multi-input multi-output systems, leading to unstable behavior and increased manufacturing costs and computation load.
Innovation Solution
A control apparatus that calculates a correlation parameter to determine the increasing/decreasing rate and direction of control inputs, ensuring convergence to target values without oscillation, and uses this parameter to manage interactions between control inputs in multi-input multi-output systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional control algorithms are used for controlled objects with extremal characteristics, then the control system becomes unstable and accuracy degrades, but implementing complex processes and parameter maps increases device complexity and manufacturing costs
Solution Approach 1:
The patent changes the parameter representation from complex multi-dimensional parameter maps to simple correlation coefficients between control inputs and controlled variables. By calculating correlation parameters that indicate the degree of correlation between each control input and controlled variable, the system adapts to extremal characteristics without requiring complex lookup tables or extensive parameter maps, thus maintaining reliability while reducing device complexity
Solution Approach 2:
The patent replaces the mechanical approach of using extensive parameter maps and complex control programs with a computational approach based on correlation analysis. Instead of storing and searching large amounts of mapping data, the system computes correlation parameters in real-time to determine control input adjustments, substituting mechanical data storage with algorithmic processing that reduces both program size and manufacturing costs
2Reliability
If conventional control algorithms are used for multi-input multi-output systems, then interaction between control inputs causes unstable behavior and degraded convergence rate, but compensating with extensive parameter maps increases manufacturing costs
Solution Approach 1:
The patent transforms the control approach by changing from fixed parameter maps to dynamic correlation parameters. For each control input, a correlation parameter is calculated that reflects its current relationship with the controlled variable. This allows the system to automatically adapt to interactions between multiple control inputs without requiring extensive manufacturing of lookup tables, thereby maintaining stability while reducing manufacturing costs
Solution Approach 2:
The patent introduces dynamic adaptation by continuously calculating correlation parameters based on current system state. Instead of using static parameter maps that require extensive manufacturing and storage, the system dynamically determines the appropriate control input adjustments by evaluating correlation coefficients, allowing it to handle multi-input interactions adaptively without increasing manufacturing complexity
3Manufacturing precision
If target values are set beyond extremum values of controlled variables, then the controlled variable cannot reach the target value causing large deviation, but conventional algorithms continue to calculate control inputs in the wrong direction
Solution Approach 1:
The patent implements feedback through correlation parameter calculation that monitors the relationship between control inputs and controlled variables. By calculating the correlation coefficient and observing its sign changes, the system receives feedback about whether the controlled variable is approaching or moving away from extremum values. This feedback mechanism allows the system to detect when the target value is unattainable and adjust the control direction accordingly, preventing large deviations and maintaining both accuracy and stability
Data Source
AI summary
A control apparatus which is capable of ensuring both high-level stability and accuracy of control and reducing manufacturing costs thereof and computation load thereon, even when controlling a controlled object having extremal characteristics or a controlled object of a multi-input multi-output system. The control apparatus is comprised of an onboard model analyzer and a cooperative controller. The onboard model analyzer, based on a controlled object model defining the relationships between an intake opening angle and an exhaust reopening angle, and an indicated mean effective pressure, calculates first and second response indices and indicative of a correlation therebetween, respectively. The cooperative controller calculates the intake opening angle and the exhaust reopening angle with predetermined algorithms such that the indicated mean effective pressure is caused to converge to its target value, and determines the increasing/decreasing rate and the increasing/decreasing direction of the aforementioned angles according to the first and second response indices.