Optimization of the mechatronic design for multi-axes drive systems

在多轴驱动系统的设计过程中，驱动系统工程师必须科普从市场上大量可用的驱动组件中选择最佳组件的挑战，这些组件的参数规格有限。主要目标是设计一个伺服系统，具有高带宽的控制。传统的系统通常使用由电流、速度和位置控制组成的嵌套控制，由于从环路到环路的带宽损失，这不是最优的。为了设计低振动的定位系统，经常使用刚性且因此大多昂贵的部件。然而，不断增加的成本压力需要在优化的多变量控制和部件的刚性之间进行权衡。在设计阶段，这种新的方法需要一个控制工程分析方面的系统的本征模式的可观性和可控性，以估计带宽。位置的可观测性的决定因素是（位置）测量系统的位置和数量，对于传统的嵌套控制回路，其限于一个编码器和一个线性长度测量系统。由此产生的某些状态的不可观测性导致不可控的状态，从而降低带宽。前一个项目已经开发了一种优化方法，该方法从具有建模不确定性的模型中估计和优化最大机械带宽。通过带有组件模型的数据库进行黑盒优化，可以在预定义的价格范围内进行快速设计。然而，这种优化是基于传统的单轴嵌套控制与过滤器。后续项目的想法是扩展多轴多变量控制的驱动器设计程序。此外，除了增加带宽外，还可以考虑多轴效应（如移动支架的偏航和俯仰）。因此，各种方法的控制工程驱动优化细化：与相对增益阵列的优化的帮助下，传感器的位置和选择，从而系统的可观测性和可控性应显着改善。现代控制方法如H∞控制或LQG控制是多输入多输出控制系统的基础。验证在带有实时控制系统的测试机上进行，该系统可评估其他直接测量系统并控制逆变器的占空比。

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.