Sensor-to-Actuator Inverse Mapping for Complex Rule Control
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Solution Overview
Problem
Traditional rule-based systems are limited in scope and complexity, struggling to generate efficient and reliable inverse mappings from forward mappings, which are essential for controlling physical actuators and classifying complex systems.
Innovation Solution
An automatic method for generating inverse mapping rules from forward mapping specifications, using a programmed computer system to process input and output parameters, and optimizing the selection of input parameters for efficient rule subset generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional rule-based systems are used for mapping, then the system structure is simple, but the scope and complexity handling capability are limited
Solution Approach 1:
The patent segments the inverse mapping generation process into distinct modules: forward mapping specification processing, input-output parameter identification, rule subset generation, and optimization. This segmentation allows the system to handle complex mappings by breaking them down into manageable rule subsets that can be processed independently and combined to form the complete inverse mapping.
Solution Approach 2:
The patent introduces an intermediary computational framework that translates forward mapping specifications into inverse mapping rules. This intermediary system uses automated algorithms to generate rule subsets and optimize parameter selection, serving as a bridge between simple forward mappings and complex inverse mapping requirements without requiring direct complex system design.
2Adaptability or versatility
If more rules are added to expand system scope, then the adaptability improves, but the system complexity increases
Solution Approach 1:
The patent applies partial action by generating rule subsets that cover only the necessary portions of the mapping space required for specific applications. Instead of creating a complete exhaustive rule set, the system generates minimal sufficient rule subsets tailored to particular input-output parameter combinations, reducing overall complexity while maintaining adequate coverage for intended uses.
Solution Approach 2:
The patent implements dynamic rule subset generation that adapts to different mapping requirements. The system can dynamically create, modify, and optimize rule subsets based on specific application needs, allowing the rule set complexity to adjust rather than being fixed. This dynamic approach enables the system to maintain low complexity for simple applications while providing the capability for high complexity when needed.
3Productivity
If automated inverse mapping generation is implemented, then productivity improves, but the computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-identifying and organizing input-output parameter relationships before generating the actual inverse mapping rules. The system performs preliminary analysis of the forward mapping specification to extract relevant parameters and their relationships, preparing the groundwork for efficient rule subset generation. This preliminary organization reduces the computational burden during the actual rule generation phase.
Solution Approach 2:
The patent utilizes parameter changes by optimizing the selection and weighting of input-output parameters during rule subset generation. The system dynamically adjusts parameter importance and transforms parameter representations to simplify the computational process. By changing how parameters are represented and prioritized, the system achieves efficient inverse mapping generation without requiring excessively complex computational algorithms.
Data Source
AI summary
An inverse mapping rule is generated from a set of forward mapping rules. The set of forward mapping rules is input. A set of output parameters for the inverse mapping rule is determined based at least in part on limiting the set of output parameters to be a subset of parameters for the set of forward mapping rules. A set of input parameters for the inverse mapping rule is determined based at least in part on limiting the set of input parameters to be: output parameters and input parameters of the set of forward mapping rules. The inverse mapping rule is generated for an input value combination. Values of output parameters of the set of forward mapping rules are determined based at least in part on the input value combination and the set of forward mapping rules. A rule consequent of the inverse mapping rule is determined at least in part by resolving values of a specified output parameter from the set of output parameters for the inverse mapping rule from the input value combination. A rule antecedent of the inverse mapping rule is determined at least in part by resolving values of a specified input parameter from the set of input parameters for the inverse mapping rule from the determined values of output parameters of the set of forward mapping rules. The inverse mapping rule is output. Input is received from a sensor. A physical actuator is controlled based at least in part on the inverse mapping rule and the input from the sensor.