With the current trend of increasing automation, leading to self-organizing machine tools and production machines (“Industry 4.0”), data acquisition and processing becomes more and more important. Based on these data, new monitoring functions and identification methods can be implemented in the machine control. Depending on the algorithms, also drive internal data, such as the actual torque, or the power consumption of the machine axes are required, partially at high sample rates. State of the art computerized numerical controllers (e.g. SIEMENS 840D sl) however, are characterized by a separation of drive system and controller. Drive data, which is not included in the standard bus-connection are difficult to access by the superordinated CNC. The paper addresses this problem, presents and compares various concepts of drive data transfer to a standard industrial CNC/PLC. Subsequently, the most convenient method, which utilizes a drive-internal data recorder is chosen for implementation. It offers flexible drive data acquisition through the PLC at high sample rates, carried out block wise. Experimental results are shown to prove the functionality. Finally, ideas for continuative monitoring and identification methods are discussed.
The position controller cascade is widely used in standard industrial controllers. Its controller parameterisation is commonly performed by either applying basic tuning rules or by carrying out not comprehensible design automatisms.In this paper an alternative approach to parameterise the cascade in one step is presented. It bases on established methods within the field of optimisation research specifically the so-called simulation-based optimisation (SBO), which can also handle non-linear models and various constrains. Own research showed, that criteria in the time domain as well as in the frequency domain are suitable optimisation criteria. However, both types have individual advantages and disadvantages. Therefore, in this research, selected representatives from both types were combined as new multi-objective optimisation criteria and investigated according to their performance. Investigations were performed for a test rig model (third order transfer function plus dead time and friction).The paper presents fundamentals of the SBO and a description of the optimisation criteria, obtained results as well as their verification on the test rig. Also, the derived controller parameterisations are compared to the integrated tuning automatism.
For the tuning of servo controllers as well as for monitoring functions, significant parameters of the controlled system are required. In contrast to identification methods with determined input signals, the paper focuses on the problem of identification with regular process movements (non-invasive identification), leading to a lack of power density in some frequency ranges. A nonlinear Least Squares (LS) approach with single mass system and friction characteristic is investigated regarding the accomplishable accuracy and necessary constraints. The proposed method is applicable on industrial motion controllers and has been carried out with a multitude of input sequences. To verify the performance of the approach, achieved experimental results for the model parameters are exposed.
The controller parameterization is often carried out by applying basic empirical formulas within an integrated automatic design. Hence, the determined settings are often insufficiently verified by the resulting system behavior. In this paper an approach for the controller parameterization by using methods of simulation based optimization is presented. This enables the user to define specific restrictions e.g. the complementary sensitivity function (CSF) to influence the dynamic behavior of the control loop. Furthermore it is possible to choose alternative optimization criteria. A main influence factor for practical offline as well as controller internal optimization methods is the execution time, which can be reduced by applying a hybrid optimization strategy. Thus, the paper presents a performance comparison between the straight global Particle-Swarm-Optimization (PSO) algorithm and the combination of the global PSO with the local optimization algorithm of Nelder-Mead (NM) to a hybrid optimizer (HO) based on examples.
Today, a cascaded system of position loop, velocity loop and current loop is standard in industrial motion controllers. The exact knowledge of significant parameters in the loops is the basis for the tuning of the servo controllers. A new method to support the commissioning has been developed. It enables the user to identify the moment of inertia as well as the time constant of the closed current loop simultaneously. The method is based on the auto relay feedback experiment by Aström and Hägglund. The model parameters are automatically adjusted according to the time behaviour of the controlled system. For this purpose, the auto relay feedback experiment is combined with the technique of gradual pole compensation. In comparison to other existing methods, this approach has the advantage that a parametric model for the open velocity loop is derived directly.
PL
We współczesnych przemysłowych układach sterowania ruchem standardowo wykorzystuje się kaskadowe systemy z pętlą sterowania położeniem, prędkością i pętlą prądową. Dokładna znajomość istotnych parametrów pętli jest podstawą dla optymalizacji działania serworegulatorów. Autorzy opracowali nową metodę wspomagającą pozyskiwanie tych danych. Umożliwia ona jednoczesną identyfikację momentu bezwładności i stałej czasu w zamkniętej pętli prądowej. Metoda jest oparta na eksperymencie Aströma i Hägglunda z automatycznym przekaźnikowym sprzężeniem zwrotnym. Parametry modelu są dobierane automatycznie, biorąc pod uwagę właściwości sterowanego systemu w dziedzinie czasu. Wykorzystano w tym celu eksperyment z automatycznym przekaźnikowym sprzężeniem zwrotnym w połączeniu z techniką stopniowej kompensacji biegunów. W porównaniu do innych istniejących metod, zaletą takiego podejścia jest możliwość bezpośredniego wyznaczenia modelu parametrycznego dla otwartej pętli sterowania prędkością.
The paper presents an adapted least squares identification method for reduced-order parametric models. On the example of the open velocity loop, different model approaches were implemented in a motion control system. Furthermore, it is demonstrated how the accuracy of the method can be improved. Finally, experimental results are shown.
PL
W artykule przedstawiono metodę identyfikacji, wykorzystującą metodę najmniejszych kwadratów, przystosowaną do modeli parametrycznych ograniczonego rzędu. Na przykładzie otwartej pętli regulacji prędkości zilustrowano różne podejścia do modelowania systemów sterowania. Zademonstrowano ponadto, jak można poprawić dokładność metody. W końcowej części pracy przedstawiono wyniki doświadczalne.
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