Christian D. Heise

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A position tracking controller for a hexacopter is presented which is robust against disturbances like modeling errors or propulsion efficiency degradation. The presented controller stands out because of its simple design which does not resort to reconfiguration and avoids the necessity of a Failure Detection and Isolation (FDI) filter. The baseline(More)
In this paper, a novel Linear Matrix Inequality (LMI) condition for Uniform Ultimate Boundedness (UUB) of Model Reference Adaptive Control with σ-Modification in the presence of unmatched parametric uncertainties is presented. Due to the presence of unmatched uncertainties and due to the usage of the σ-Modification, the control objective of(More)
In this paper a novel stability proof for direct Model Reference Adaptive Control is presented. Especially the case of redundant inputs is taken into account in order to consider actuator failures and even change in the control direction. To this end, a weaker assumption than positive definiteness of the control effectiveness matrix is formulated.(More)
In this paper, novel control and update laws for predictor-based Model Reference Adaptive Control for the case of over-actuated systems are presented. A weaker assumption than positive definiteness of the control effectiveness matrix is formulated. This allows to take actuator failures and even changes in the control direction into account. Furthermore, it(More)
This paper deals with the computation of timedelay margins of state feedback Model Reference Adaptive Control (MRAC) with σ -modification for single input Linear Time Invariant (LTI) plants. Unlike previous results dealing with the computation of time-delay margins, a direct MRAC (without specific modification to accommodate for the timedelay) is considered(More)
A new efficient adaptive optimal control approach is presented in this paper based on the indirect model reference adaptive control (MRAC) architecture for improvement of adaptation and tracking performance of the uncertain system. The system accounts here for both matched and unmatched unknown uncertainties that can act as plant as well as input(More)
In this paper, two approaches for model following control in the presence of uncertainties are compared. Specifically, the so-called command governor framework, originally developed as an augmentation to adaptive control, and a modified linear extended state observer are evaluated. Both approaches estimate the disturbance signal causing the plant to deviate(More)
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