Rotorcraft flight control design using quantitative feedback theory and dynamic crossfeeds

A multi-input, multi-output controls design with robust crossfeeds is presented for a rotorcraft in near-hovering flight using quantitative feedback theory (QFT). Decoupling criteria are developed for dynamic crossfeed design and implementation. Frequency dependent performance metrics focusing on piloted flight are developed and tested on 23 flight configurations. The metrics show that the resulting design is superior to alternative control system designs using conventional fixed-gain crossfeeds and to feedback-only designs which rely on high gains to suppress undesired off-axis responses. The use of dynamic, robust crossfeeds prior to the QFT design reduces the magnitude of required feedback gain and results in performance that meets current handling qualities specifications relative to the decoupling of off-axis responses. The combined effect of the QFT feedback design following the implementation of low-order, dynamic crossfeed compensator successfully decouples ten of twelve off-axis channels. For the other two channels it was not possible to find a single, low-order crossfeed that was effective

A High-Order, Linear Time-Invariant Model for Application to Higher Harmonic Control and Flight Control System Interaction

This research describes a new methodology for the extraction of a high-order, linear time invariant model, which allows the periodicity of the helicopter response to be accurately captured. This model provides the needed level of dynamic fidelity to permit an analysis and optimization of the AFCS and HHC algorithms. The key results of this study indicate that the closed-loop HHC system has little influence on the AFCS or on the vehicle handling qualities, which indicates that the AFCS does not need modification to work with the HHC system. However, the results show that the vibration response to maneuvers must be considered during the HHC design process, and this leads to much higher required HHC loop crossover frequencies. This research also demonstrates that the transient vibration responses during maneuvers can be reduced by optimizing the closed-loop higher harmonic control algorithm using conventional control system analyses

A High-Order, Time Invariant, Linearized Model for Application to HHCIAFCS Interaction Studies

This paper describes a methodology for the extraction of a linear time invariant model from a nonlinear helicopter model, and followed by an examination of the interactions of the Higher Harmonic Control (HHC) and the Automatic Flight Control System (AFCS). This new method includes an embedded harmonic analyzer inside a linear time invariant model, which allows the periodicity of the helicopter response to be captured. The: coupled high-order model provides the needed level of dynamic fidelity to permit an analysis and optimization of the AFCS and HHC loops. Results of this study indicate that the closed-loop HHC system has little influence on the AFCS or on the vehicle handling qualities, which indicates that the AFCS does not need modification to work with the HHC system. The results also show that the vibration response to maneuvers must be considered during the HHC design process, which leads to much higher required HHC loop crossover frequencies. This research also demonstrates that the transient vibration response during maneuvers can be reduced by optimizing the closed-loop higher harmonic control laws using conventional control system analyses

The evolution of living beings started with prokaryotes and in interaction with prokaryotes

In natural world, no organism exists in absolute isolation, and thus every organism must interact with the environment and other organisms. Next-generation sequencing technologies are increasingly revealing that most of the cells in the environment resist cultivation in the laboratory and several prokaryotic divisions have no known cultivated representatives. Based on this, we hypothesize that species that live together in the same ecosystem are more or less dependent upon each other and are very large in diversity and number, outnumbering those that can be isolated in single-strain laboratory culture. In natural environments, bacteria and archaea interact with other organisms (viruses, protists, fungi, animals, plants, and human) in complex ecological networks, resulting in positive, negative, or no effect on one or another of the interacting partners. These interactions are sources of ecological forces such as competitive exclusion, niche partitioning, ecological adaptation, or horizontal gene transfers, which shape the biological evolution. In this chapter, we review the biological interactions involving prokaryotes in natural ecosystems, including plant, animal, and human microbiota, and give an overview of the insights into the evolution of living beings. We conclude that studies of biological interactions, including multipartite interactions, are sources of novel knowledge related to the biodiversity of living things, the functioning of ecosystems, the evolution of the cellular world, and the ecosystem services to the living beings