Machine Control System Using Dual Models and Feedback
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Solution Overview
Problem
Existing control systems for machines like generators and motors often rely on trial and error or generic programming, which are inefficient and fail to accurately adapt to the unique operating characteristics of individual machines, especially in varying environmental conditions and over time due to changes such as friction and corrosion.
Innovation Solution
A control system that uses two models and a feedback loop to generate and refine control signals based on measured and predicted parameters, allowing for real-time adjustment and optimization of machine operation, with a comparator ensuring that predetermined thresholds are met to switch between controllers or models for continuous refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If trial and error control method is used, then the control system is simple to implement, but it requires more time to achieve desired operating level and results in excessive hunting
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing optimal control signals in lookup tables before operation. The controller retrieves pre-computed control actions based on current state, eliminating the need for real-time trial and error iterations. This resolves the contradiction by providing fast response (reducing time loss) while maintaining relatively simple hardware (the lookup table structure).
Solution Approach 2:
The patent uses preliminary action by pre-computing control strategies offline and storing them in memory structures. During operation, the controller simply retrieves pre-calculated control signals based on measured parameters, avoiding real-time iterative computation. This achieves fast response time while keeping the online controller relatively simple.
2Device complexity
If trial and error control method is used, then the control system is simple to implement, but it results in excessive hunting until machine stabilizes
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing optimal control signals in lookup tables before operation. The controller retrieves pre-computed control actions based on current state, eliminating the need for real-time trial and error iterations. This resolves the contradiction by providing fast response (reducing time loss) while maintaining relatively simple hardware (the lookup table structure).
3Adaptability or versatility
If generic programming is used to model machine operation, then the control system can be applied to entire class of machines, but it cannot accurately adapt to individual machine characteristics
Solution Approach 1:
The patent applies local quality by creating individualized lookup tables for each specific machine based on its unique characteristics. While the overall control architecture remains generic and can be applied to an entire class of machines, each machine receives customized control parameters stored in its lookup table. This resolves the contradiction by enabling accurate adaptation to individual machines without requiring completely custom control systems for each unit.
Solution Approach 2:
The patent uses preliminary action by pre-characterizing each individual machine during setup or commissioning, then storing its specific parameters in lookup tables. This offline customization allows the generic controller hardware to adapt to individual machine characteristics without requiring complex real-time adjustment mechanisms, thus maintaining relatively simple device complexity while achieving high adaptability.
4Measurement precision
If control programming is specifically tailored to each individual machine, then accurate control is achieved, but the device complexity and programming effort increase significantly
Solution Approach 1:
The patent applies local quality by creating individualized lookup tables for each specific machine based on its unique characteristics. While the overall control architecture remains generic and can be applied to an entire class of machines, each machine receives customized control parameters stored in its lookup table. This resolves the contradiction by enabling accurate adaptation to individual machines without requiring completely custom control systems for each unit.
Solution Approach 2:
The patent uses copying by creating standardized lookup table structures that can be replicated across multiple machines. Once a lookup table is created and validated for one machine, the same template can be copied and adapted for other machines in the same class, reducing programming effort. This allows high control accuracy through individualization while maintaining efficiency through template copying.
Data Source
AI summary
A system for controlling a machine includes a first model, a second model, a controller, and a comparator. During a first cycle, the first model generates a response signal to the controller while the second model generates a predicted parameter signal. During the first cycle, the comparator transmits a feedback signal to the second model if a predetermined threshold is not met. A method for controlling a machine includes transmitting a response signal from a first model to a controller, generating a control signal to the machine, and generating a predicted parameter value in a second model. The method further includes transmitting a feedback signal to the second model if a predetermined threshold is not met.