4 research outputs found
Robust and Cooperative Formation Control of Nonlinear Multi-Agent Systems
Compared with the conventional approach of controlling autonomous systems individually, building up a cooperative multi-agent structure is more robust and efficient for both research and industrial purposes. Among the many subbranches of multiagent systems, formation control has been a popular research direction due to its close connection with complex missions such as spacecraft clustering and intelligent transportation. Hence, this thesis focuses on providing new robust formation control algorithms for first-order, second-order and mixed-order nonlinear multi-agent systems to construct and maintain stable system structure in practical scenarios. System uncertainties and external disturbances are commonly seen factors that could negatively affect the formation tracking precision. Among the many popular tools of uncertainty estimation, the implementation of approaches including neural network adaptive estimation and observer-based approximation are discussed in this thesis. Regarding the neural-based approximation process, different neural network structures including Chebyshev neural network, radial basis function neural network, twolayer artificial neural network and three-layer artificial neural network are tested and implemented. The merits and drawbacks of each network design in the field of control is then analysed. Apart from that, this thesis also offers detailed comparison between the cooperative tuning approach and the observer-based tuning approach regarding the neural network structure to find their corresponding applicable scenarios. To ensure the safety of the formation control algorithms, the issues of obstacle avoidance and inter-agent collision avoidance are both considered. Although the method of constructing artificial potential fields is a popular approach in both the field of path planning and motion control, few have discussed the effect of the inter-agent communication on the collision avoidance scheme. For the obstacle avoiding scenarios, the passive correcting behaviour of individual agent is defined and investigated. A new algorithm is then introduced to modify the reference of individual agents to act as the mitigation. The issue of insufficient information accessibility is then discussed for multi-agent systems with a static and uncompleted communication topology. A distance-based communication topology is proposed to create necessary information exchange channel for unconnected agent pairs that are close enough. The actuator saturation issue is also considered for both first-order multi-agent systems and second-order multi-agent systems to increase the practicality of the formation control schemes. Apart from restricting the amplitudes of the control input, the effect of the input coupling phenomenon is investigated. The oscillation of states brought by the coupled and saturated control input is then summarised as the reverse effect. To attenuate the state oscillation, the methods of developing control input regulation algorithms and employing auxiliary compensator are discussed and validated. The last technical problem to discuss is the hierarchical control scheme. The issue of how to decouple the inter-agent communication and the motion dynamics is discussed for both unified-order and mixed-order multi-agent systems. By using a hierarchical formation control structure, the inter-agent communication process is considered based on a group of virtual agents with ideal characteristics, which can significantly reduce the complexity of the system design. Adaptive hierarchical control schemes are then proposed and validated for both unified-order and mixed-order multi-agent systems through the examples of a multi-drone system and a multiple omni-directional robot system, respectively.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 202
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Studies on assembly and genetic variation in mitochondrial respiratory complex I
Complex I (NADH:ubiquinone oxidoreductase) couples electron transfer to proton translocation across the inner mitochondrial membrane, to drive the synthesis of ATP. Its distinctive L-shaped structure comprises 45 subunits, encoded by both the mitochondrial and nuclear genomes, which are assembled by a complicated modular pathway. Complex I genetic defects are the most common cause of mitochondrial disorders and often present in early childhood, with high mortality rates. Recent high-resolution electron cryo-microscopy structures of mammalian complex I provide a foundation for both interpreting biochemical and biomedical data and understanding the catalytic mechanism.
First, this thesis explores how the flavin cofactor is inserted into the NADH-binding (N-) domain of complex I. Genetic manipulation of cultured human cells, to starve them of flavin, revealed a hierarchal impact on the mitochondrial flavoproteome. High riboflavin content in the growth media ameliorated observed phenotypes, requiring cell conditioning in low riboflavin conditions. CRISPR knockout of the putative mitochondrial flavin transporter SLC25A32 demonstrated the severe impact of decreased flavin on complexes I and II, and mass spectrometry ‘complexome’ analyses suggest that the N-domain is still assembled onto complex I in the absence of the flavin.
Second, the model organism Yarrowia lipolytica was used to assess the importance of residues in the quinone-binding site of complex I. Three residues with proposed roles in binding the quinone head-group were targeted. One variant was catalytically inactive, while two retained some activity. They showed decreased ability to reduce physiologically-relevant, long chain quinones, but their ability to reduce short-chain analogues was affected less severely. The results suggest a complicated picture in which interactions between the protein and both the hydrophilic quinone head-group and hydrophobic isoprenoid chain contribute to quinone-binding affinity and catalysis.
Finally, a model for human complex I, generated from a recent high-resolution structure of mouse complex I, was used to investigate whether the pathogenicity of human variants could be predicted. Structural information on variant residues, including their secondary structure, proximity to key features and surface exposure, was collated and the power of each property to predict pathogenicity investigated. The analysis was then extended to the whole structure, to identify potential pathogenic hotspots in the enzyme, inform future studies of functionally important regions in complex I, and aid the diagnosis of clinically relevant pathogenic variants