Optimization of the mechatronic design for multi-axes drive systems

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During the design process of multi-axis, drive systems engineers have to cope with the challenge of selecting optimal components out of a large number of available drive components on the market with only limited parameter specifications. The main objective is the design of a servo system with a high bandwidth in the control. Conventional systems usually use a nested control consisting of current, speed and position control, which is not optimal due the bandwidth loss from loop to loop. In order to design low-vibrating positioning systems, stiff and thus mostly expensive components are often used. However, the increasing cost pressure requires a trade-off between optimized multi-variable control and rigidity of the components. During the design phase, this new approach needs a control engineering analysis with regard to observability and controllability of the system’s eigen modes in order to estimate the bandwidth. A determining factor for the observability of the position is the location and number of the (position) measuring systems, which are limited to one encoder and one linear length measuring system for the conventional nested control loop. The resulting non-observability of certain states leads to uncontrollable states and thus to lower bandwidths. The predecessor project has already developed an optimization method, which estimates and optimizes the maximum mechanical bandwidth from a model with modelled uncertainties. A black box optimization via a database with component models enables a fast design for a predefined price range. However, this optimization was based on the conventional uniaxial nested control with filters. The idea of the subsequent project is to extend the drive design procedure for a multi-axial multi-variable control. Moreover, besides increasing the bandwidth, multiaxial effects (such as yawing and pitching of travel stands) can also be taken into account. Therefore, various methods of control engineering for drive optimization are refined: With the help of an optimization of the relative gain array, the sensor positions and selections and thus the observability and controllability of systems shall be improved significantly. Modern control methods such as H∞ or LQG control are the basis for the multiple input and multiple output control system. The validation takes place on on a test machine with a real-time control system, which evaluates additional direct measuring systems and controls the duty cycles of the inverters.