Servo Mechatronic Simulation via Precomputed Dynamics Database
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Solution Overview
Problem
Designing a servo driven mechatronic system is complex due to unknown system dynamics and the need for extensive prototyping and simulation software constraints, leading to high costs and lengthy lead times, with users requiring expertise in selecting and configuring hardware components.
Innovation Solution
A system and method for simulating a servo driven mechatronic system that allows users to select and configure components from a database, providing a graphical representation for tuning and analysis, enabling fast simulation of various designs without prototyping, and integrating with industrial controller databases for comprehensive simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If general simulation software is used to simulate servo driven mechatronic systems, then simulation capability is provided, but the system requires large amounts of design information that is unknown at design time and has narrow constraints
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing system dynamics characteristics for various motor-load combinations in a database before the actual design process. This allows the simulation software to retrieve pre-computed dynamics rather than requiring users to provide all design information upfront, resolving the contradiction between simulation capability and design information requirements
Solution Approach 2:
The system creates simplified copies of complex servo driven system dynamics by pre-computing and storing dynamic characteristics in a database. These copied dynamics models can be directly used in simulation without requiring users to have deep expertise or provide extensive design information, making the simulation process more accessible while maintaining accuracy
2Measurement precision
If prototype machines are built and empirical tests are conducted to determine proper combinations of machinery and configuration parameters, then accurate system performance data is obtained, but large expense and lengthy lead times are incurred
Solution Approach 1:
The system performs preliminary simulations and computations to predict system performance before physical prototyping. By pre-calculating motor-load dynamics and providing accurate performance data through simulation, the system eliminates the need for expensive and time-consuming empirical testing while maintaining measurement precision
Solution Approach 2:
The system replaces the mechanical prototyping and empirical testing process with a computational simulation system. By substituting physical experiments with virtual simulations that use pre-computed dynamics models, the system achieves the same measurement precision without the time loss and expense associated with building and testing physical prototypes
3Adaptability or versatility
If users manually select and configure hardware components and parameters for servo driven systems, then system customization is achieved, but extensive user expertise is required
Solution Approach 1:
The system provides self-service by automatically selecting appropriate motor-load combinations and configuring optimal parameters based on user specifications. The database contains pre-analyzed dynamics characteristics that enable the system to autonomously make configuration decisions, maintaining full customization capability while eliminating the need for users to have extensive servo system expertise
Solution Approach 2:
The system introduces an intermediary layer (the database of pre-computed dynamics and the automated selection algorithm) between the user and the complex hardware configuration. This intermediary handles the expertise-intensive tasks of component selection and parameter tuning, allowing users to customize systems without needing deep technical knowledge of servo driven mechanics
Data Source
AI summary
A servo driven mechatronic system simulator and analyzer utilizing preconfigured motion equipment profile databases to predict the behavior of a motion system based on a user selected configuration. The user can adjust the parameters and rerun the simulation and analysis many times in an efficient manner until the optimum operating conditions of the desired system are reached. The user can then archive the system design and implement the system with a greater level of confidence in the ability of the design to meet the requirements of the application.