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.

The paper presents the control concept for an experimental rig with closed-loop controlled pneumatic axis. The objective is the convenient execution of diverse control technologic experiments using free implementable control structures. Since two actuators can be mechanically linked to one another, one is force controlled to generate defined disturbances. Furthermore, a particular simulation model, which can be integrated in the controllers' user program, is pointed out including non-linear effects. Finally, selected experiments are discussed.

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.

The paper describes a nonlinear controller design technique applied to a servo drive in the presence of hard state constraints. The approach presented is based on nonlinear state-space transformation and adaptive backstepping. It allows us to impose hard constraints on the state variables directly and to achieve asymptotic tracking of any reference trajectory inside the constraints, despite unknown plant parameters. Two control schemes (with and without integral action) are derived, investigated and then compared. Several examples demonstrate the main features of the design procedure and prove that it may be applied in case of motion control problems in electric drive automation.

One of the applications of tether system is in the field of satellite technology, where the mother ship and satellite equipment are connected with a cable. In order to grasp the motion of this kind of tether system in detail, the tether can be effectively modeled as flexible body and dealt by multibody dynamic analysis. In the analysis and modeling of flexible body of tether, large deformation and large displacement must be considered. Multibody dynamic analysis such as Absolute Nodal Coordinate Formulation with an introduction of the effect of damping force formulation can be used to describe the motion behavior of a flexible body. In this study, a parameter identification technique via an experimental approach is proposed in order to verify the modeling method. An example of swing-up control using the genetic algorithm control approach is performed through simulation and experiment. The validity of the model and availability of motion control based on multibody dynamics analysis are shown by comparison between numerical simulation and experiment.

Controlling mechanical systems with position and velocity cascade loops is one of the most effective methods to operate this type of systems. However, when using low-rate sampling electronics, the implementation is not trivial and the resulting performance can be poor. This paper proposes effective tuning rules that only require establishing the bandwidth of the inner velocity loop and an estimation of the inertia of the mechanism. Since discrete-time mechatronic systems can also exhibit unstable behavior, several stability conditions are also derived. By using the proposed methodology, a P-PI control algorithm is developed for a desktop haptic device, obtaining good experimental performance with low sampling-rate electronics.