METHOD FOR DETERMINING A CONTROLLER CONFIGURATION FOR A DRIVE SYSTEM, COMPUTER PROGRAM, COMPUTER-READABLE MEDIUM, DEVICE AND DRIVE SYSTEM

Abstract

A controller configuration for a drive system with a drive is determined using at least one simulation model. One or more controlled system measurement results are received. One or the respective controlled system measurement result is obtained by measuring an RPM speed control loop of the drive system. A simulation model with a drive unit submodel and with one or more controlled system submodels is created for the or the respective RPM speed control loop. A system identification is carried out using the or the respective controlled system measurement result in order to obtain the or the respective controlled system submodel. A controller configuration is determined for the drive system using the simulation model.

Claims

1.-15. (canceled)

16. A method for determining a controller configuration for a drive system with a drive using at least one simulation model, the method comprising: obtaining a plurality of controlled system measurement results associated with different RPM speed control loops, which differ in respect of at least one component and are of different design, by measuring the RPM speed control loops of the drive system; receiving the one or more controlled system measurement results; carrying out a system identification in order to obtain controlled system submodels using the controlled system measurement results by providing a controlled system submodel with unknown model parameters and determining the model parameters using the controlled system measurement results and using a mathematical optimization method to approximate the model parameters so that the model parameters correspond to the controlled system measurement results; creating a simulation model with a drive submodel and with a controlled system submodel created for each of the RPM speed control loops; and determining an averaged controller configuration as a common controller configuration for the drive system using the simulation model, the common controller configuration suitable for all of the RPM speed control loops and stable for all of the RPM speed control loops.

17. The method of claim 16, wherein the controlled system measurement results comprise at least one metrologically acquired frequency response of the RPM speed control loops.

18. The method of claim 16, wherein the mathematical optimization to approximate the model parameters is according to a quality criterion defined by the user.

19. The method of claim 16, further comprising obtaining controlled system measurement results by measuring the RPM speed control loop after a defined excitation.

20. The method of claim 19, wherein the defined excitation is a defined noise excitation, preferably after a pseudo-random noise excitation.

21. The method of claim 20, wherein the defined noise excitation is a pseudo-random noise excitation.

22. The method of the claim 16, further comprising defining, for the system identification, a number of poles and zeros for the or the controlled system measurement results, and/or determining a number of poles and zeros in the controlled system measurement results.

23. The method of the claim 16, further comprising iteratively adjusting the model parameters in the system identification for controlled system submodels.

24. The method of claim 23, further comprising iteratively adjusting the model parameters until a desired result is obtained.

25. The method of claim 16, further comprising creating the drive submodel using known drive parameters.

26. The method of claim 16, further comprising creating the drive submodel using known drive parameters of a motor of the drive.

27. The method of claim 16, further comprising determining the controller configuration for a drive system with a drive using at least one simulation model independently of the operation of the drive system, and/or without access to the drive system.

28. The method of claim 16, further comprising simulating and verifying discrete control loops using the simulation model in determining the averaged controller configuration.

29. The method of claim 16, further comprising controller parameters and current setpoint filters for the drive system comprising the determined averaged controller configuration and/or transferring the determined controller configuration to the drive system and controlling the drive system accordingly.

30. The method of claim 16, further comprising controller parameters and current setpoint filters for the drive comprising the determined averaged controller configuration.

31. A non-transitory computer-readable medium storing a computer program comprising instructions which, when executed on at least one computer, cause the at least one computer to carry out the method of claim 16.

32. A device for data processing, the device comprising: a processor; and a data storage device on which computer-executable program code is stored which, when executed by the processor, causes the processor to carry out the method of claim 16.

33. A drive system, comprising: a drive; and a device for data processing the device comprising a processor, and a data storage device on which computer-executable program code is stored which, when executed by the processor, causes the processor to carry out the method of claim 16.

Description

[0046] Further features and advantages of the present invention will emerge from the following description of an embodiment according to the invention with reference to the accompanying drawing in which:

[0047] FIG. 1 is a purely schematic representation of the steps of an exemplary embodiment of the method according to the invention

[0048] FIG. 1 shows a purely schematic block diagram of a real drive system 1 with a drive 2. Also shown are three real RPM speed control loops 3 of the drive system 1 which are different from one another, specifically corresponding to three different load configurations. For example, the first RPM speed control loop 3 can correspond to an initial state at commissioning, and the two other configurations can each correspond to changed configurations as a result of, for example, retooling operations. Merely by way of example, a printing press comprising the drive system 1 is operated with three different rollers.

[0049] It should be emphasized that the number of three RPM speed control loops 3 is to be understood as purely exemplary and that it could be any given number, even a single RPM speed control loop 3.

[0050] FIG. 1 also shows an engineering platform 4 connected to the drive system 1 and a computer program 5 comprising program code means which, when executed on at least one computer, cause the at least one computer to carry out the steps described below, as also schematically illustrated in the FIGURE. The drive system 1 can comprise a device for data processing, comprising a processor and a data storage device on which corresponding computer-executable program code is stored which, when executed by the processor, causes the processor to carry out the steps described. However, such a device can also be separate from the drive system 1. For example, it can also be an edge device.

[0051] In step S1, a plurality of controlled system measurement results 6, in this case three, are received by the computer program 5 for the three RPM speed control loops 3, each of said results being obtained by measuring one of the three RPM speed control loops 3 of the drive system 1 after a defined noise excitation, in this case after a pseudo-random noise excitation. A user can import the controlled system measurement results 6 from the engineering portal 4, for example. The controlled system measurement results 6 are each representative of a metrologically acquired frequency response of the respective RPM speed control loop 3. In the present case, the frequency responses 6 have been recorded prior to step S1 using the engineering platform 4 which comprises an associated functionality in a manner known in principle. In the exemplary embodiment described here, the frequency responses 6 constituting the controlled system measurement results were recorded beforehand, in other words before the method was carried out. The steps described here can be performed completely independently of the operation of the drive system 1 and without access thereto.

[0052] In step S2, a simulation model 7 is created, comprising a drive submodel 8 and a plurality of, in this case three, controlled system submodels 9. Each controlled system submodel 9 corresponds to one of the RPM speed control loops 3. To obtain the controlled system submodels 9, a generic system identification is carried out using the respective controlled system measurement result 6. The user defines the number of poles and zeros (model complexity) that they expect for the respective RPM speed control loop 3. The system identification is then carried out. First, a controlled system submodel with unknown model parameters is provided for each RPM speed control loop 3 and the model parameters are determined using the respective controlled system measurement result 6. For this purpose, the corresponding model parameters are adjusted using a numerical optimization algorithm until the curves of the frequency characteristics of the controlled system measured match as closely as possible the one modelled or meet quality criteria specified by the user.

[0053] As soon as the RPM speed control loops 3, in other words the mechanical systems and the mechanical behavior, have been identified, motor data such as motor type, pole pair count and motor constants for the drive 2 are transferred from the engineering platform 4 or manually by the user and an associated drive submodel 8 is created, in particular as a representation of the control and regulation of the converter using known drive parameters. The drive submodel 8 and its parameterization are advantageously implemented in an identical manner to the real drive. In this process, the time characteristics of the controller cascade and all the filters involved are preferably also re-implemented analogously to the real model.

[0054] In step S3, discrete control loops are simulated and verified using the simulation model 7 incorporating the drive submodel 8 and the controlled system submodels 9, and a suitable controller configuration 10 for the drive system 1 is determined. The frequency characteristics of the open and closed control loops of the optimized system are presented for validation by the user following optimization. The optimized system refers specifically to the overall system comprising the drive 2 and controlled system(s) 3 after optimization of the controller parameters. The optimized parameters have preferably been incorporated into the drive submodel 8 and the optimized system re-simulated. Simulations within the simulation model 7 can be implemented with the respective previously identified controlled system submodels 9 in order to verify the time response of the optimized system for different application-oriented situations and applications. For example, step responses or setpoint profiles from the real control system can be simulated.

[0055] An averaged controller configuration 10 that is stable across all three RPM speed control loops 3 is generated as a common controller configuration 10. The common controller configuration 10 comprises filter and controller settings that can govern all three RPM speed control loops 3 uniformly and provide optimized system behavior. If, for example, a different RPM speed control loop 3 is acquired due to retooling, no re-parameterization is required. The single controller configuration remains suitable.

[0056] The common controller configuration 10 can be transferred to the engineering platform 4, as indicated by an arrow in FIG. 1.

[0057] In step S4, the determined controller configuration 10 is transferred to the drive system 1 and the latter is controlled accordingly. As a result, an optimized system behavior is achieved for all three RPM speed control loops 3.

[0058] By carrying out the described procedure, downtimes for commissioning a real machine can be significantly reduced, as a virtual design and simulation of the identified controlled system(s) is possible based on a verified simulation model 7. A high level of accuracy is achieved, and this without having to intervene in operation.

[0059] Although the invention has been illustrated and described in detail by the preferred exemplary embodiment, the invention is not limited by the examples disclosed and other variations will be apparent to a person skilled in the art without departing from the scope of protection sought for the invention.