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Ellipsoidal unfalsified control is a plant-model-free, data-driven control design method. It recursively checks, using available data, whether the ability of a controller to meet a predefined performance requirement is (un)falsified. The set of unfalsified controllers is described by an ellipsoid in the control parameter space. The update of the ellipsoid employing new measurements can be computed...
This paper exploits high-resolution time-frequency analysis of servo error signals in the investigation of position-dependent dynamics in a motion system with iterative learning control. Based on the matching pursuit algorithm signals are decomposed with respect to a multiple complex dictionary of atoms. A high-resolution signal energy distribution is derived in the time-frequency plane, which does...
For systems that perform repetitive tasks, a high performance feedforward signal can be derived using iterative learning control (ELC). The feedforward signal is updated through successive iterations. Disturbances present in the control scheme, such as load and measurement disturbances, are also present in the learning process and deteriorate the performance of ILC. This paper presents an expression...
In this paper, we discuss the design of multivariable motion controllers exploiting crosscouplings in the controller for open loop decoupling, disturbance rejection and feedforward decoupling. Using specific properties of motion systems, we illustrate that frequency response design methods can be extended to handle several multivariable control problems. Application to high performance motion systems...
This paper presents recent research results for feedback control design of motion systems. Two model-free approaches are investigated, that exploit the ease of experimentation which is typical for motion systems. One approach is data-based design of a linear feedback controller which realizes desired closed-loop sensitivity and complementary sensitivity transfer functions. These transfer functions...
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