Plant Controller Dynamic Gain for Air-Fuel Stability
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Solution Overview
Problem
Conventional air-fuel ratio controllers for internal combustion engines face challenges in achieving precise control, particularly in maintaining the air-fuel ratio stability and responsiveness, due to limitations in calculating the control parameters and sensitivity to disturbances.
Innovation Solution
A feedback controller is designed with a transfer function that incorporates an inverse plant model and a disturbance sensitivity correlation function, using a sensitivity function defined by a response characteristic parameter to optimize control input and suppress disturbances, ensuring the air-fuel ratio matches a target value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional feedback control with predetermined control gain is used, then control stability is maintained, but control precision and responsiveness deteriorate
Solution Approach 1:
The control gain is transformed from a static predetermined value to a dynamic variable that changes based on operating conditions. The control gain calculation unit computes the control gain according to the plant transfer function and sensitivity function, which are determined by the response characteristic parameter varying with operating conditions. This dynamic adjustment enables the controller to adapt to changing system characteristics, improving control precision while maintaining stability across different operating ranges.
Solution Approach 2:
The invention changes the control parameter (control gain) based on the response characteristic parameter of the plant. By defining the sensitivity function using the response characteristic parameter and calculating the control gain accordingly, the system adapts its control characteristics to match the actual plant behavior under different operating conditions, thereby resolving the contradiction between stability and precision.
2Measurement precision
If model-based control is implemented, then control performance is improved, but device complexity increases
Solution Approach 1:
Instead of implementing a complex full-order model, the invention uses a simplified approach by defining the sensitivity function based on the response characteristic parameter. This parameter-based method captures the essential dynamics of the plant without requiring a complete mathematical model, thus improving control performance while avoiding excessive complexity in the controller structure.
Data Source
AI summary
A plant controller includes a feedback controller configured to calculate a control input provided to a plant so that a control output of the plant matches a target value. The feedback controller includes a controller transfer function that is a transfer function of the feedback controller. The controller transfer function is expressed by a product of an inverse transfer function of a transfer function of a control target model obtained by modeling the plant and a disturbance sensitivity correlation function defined using a sensitivity function. The sensitivity function indicates sensitivity of a disturbance to be applied to the plant with respect to the control output. The sensitivity function is defined by using a response characteristic parameter that indicates a response characteristic of the plant.