Drive Speed Loop Simulation for Controller Tuning Without Downtime
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing controller optimization methods for complex drive systems are time-consuming, require expert knowledge, and result in significant downtime due to the need for manual adjustments and continuous monitoring, especially when dealing with varying load configurations and system changes.
Innovation Solution
A method using a simulation model to determine a controller configuration based on real measurements of the drive system, allowing for optimized controller settings without requiring expert intervention, by creating a digital representation of the drive and its mechanical behavior, and simulating discrete control loops to verify the settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual optimization methods are used to determine controller settings, then the controller can be adapted to specific mechanical systems, but the process becomes very time-consuming and requires constant machine access resulting in downtime
Solution Approach 1:
The patent creates a digital twin (simulation model) that copies the essential dynamic characteristics of the mechanical system. This virtual model allows controller optimization to be performed in silico rather than requiring repeated physical machine access. The frequency response data from the real system is used to parameterize the simulation model, which then serves as a virtual testbed for iterative controller tuning without causing actual downtime.
Solution Approach 2:
The patent performs preliminary system identification by measuring the frequency response of the mechanical system once during commissioning. This data is stored and used to pre-parameterize the simulation model. Subsequent controller optimizations can then be performed using this pre-prepared model without requiring further machine access, effectively performing the optimization action in advance.
2Reliability
If specialist knowledge is used to parameterize and optimize drives, then proper controller settings can be achieved, but the complexity and time required increases significantly
Solution Approach 1:
The patent enables the system to optimize its own controller parameters automatically using the simulation model and stored frequency response data. The automated optimization algorithm iteratively adjusts controller parameters in the simulation until optimal performance is achieved, eliminating the need for specialist intervention. The system essentially performs the optimization task itself based on objective criteria rather than expert judgment.
Solution Approach 2:
The patent replaces the mechanical process of specialist analysis and manual parameter adjustment with an automated computational optimization algorithm running in the simulation model. The complex iterative process that previously required expert knowledge is substituted by an automated software-based optimization routine that systematically searches for optimal controller parameters.
3Adaptability or versatility
If continuous monitoring and adjustment during operation is performed, then system changes can be accommodated, but this requires additional time and effort
Solution Approach 1:
The patent maintains a digital twin that can be updated with new frequency response measurements when system changes occur. This virtual copy allows rapid re-optimization of controller parameters without requiring physical system intervention. The simulation model serves as a safe environment to test and validate new controller settings before applying them to the actual system, minimizing disruption to operations.
Data Source
AI summary
The invention relates to a method for determining a controller configuration (10) for a drive system (1) with a drive (2) using at least one simulation model (7), in which S1) one or more controlled system measurement results (6) are received, wherein the one or the respective controlled system measurement result (6) is obtained by measuring an RPM speed control loop (3) of the drive system (1), S2) a simulation model (7) with a drive unit submodel (8) and with one or more controlled system submodels (9) is created for the or the respective RPM speed control loop (3), wherein a system identification is carried out using the or the respective controlled system measurement result (6) in order to obtain the or the respective controlled system submodel (9), and S3) a controller configuration (10) is determined for the drive system (1) using the simulation model (7). The invention also relates to a computer program, a computer-readable medium, a device for data processing and drive system (1).