Trait Integration as a Constraint on Phenotypic Evolution

Collectively, my results highlight the utility of the P matrix as a tool for studying the integration of complex traits. The extreme stability of P in T. commodus suggests that it is likely to act as a constraint on the evolution of call structure in this species. This insight, together with the link between call structure and wing morphology, illustrates the value of treating evolution as a multivariate process

Observer-based robust fault estimation for fault-tolerant control

A control system is fault-tolerant if it possesses the capability of optimizing the system stability and admissible performance subject to bounded faults, complexity and modeling uncertainty. Based on this definition this thesis is concerned with the theoretical developments of the combination of robust fault estimation (FE) and robust active fault tolerant control (AFTC) for systems with both faults and uncertainties.This thesis develops robust strategies for AFTC involving a joint problem of on-line robust FE and robust adaptive control. The disturbances and modeling uncertainty affect the FE and FTC performance. Hence, the proposed robust observer-based fault estimator schemes are combined with several control methods to achieve the desired system performance and robust active fault tolerance. The controller approaches involve concepts of output feedback control, adaptive control, robust observer-based state feedback control. A new robust FE method has been developed initially to take into account the joint effect of both fault and disturbance signals, thereby rejecting the disturbances and enhancing the accuracy of the fault estimation. This is then extended to encompass the robustness with respect to modeling uncertainty.As an extension to the robust FE and FTC scheme a further development is made for direct application to smooth non-linear systems via the use of linear parameter-varying systems (LPV) modeling.The main contributions of the research are thus:- The development of a robust observer-based FE method and integration design for the FE and AFTC systems with the bounded time derivative fault magnitudes, providing the solution based on linear matrix inequality (LMI) methodology. A stability proof for the integrated design of the robust FE within the FTC system.- An improvement is given to the proposed robust observer-based FE method and integrated design for FE and AFTC systems under the existence of different disturbance structures.- New guidance for the choice of learning rate of the robust FE algorithm.- Some improvement compared with the recent literature by considering the FTC problem in a more general way, for example by using LPV modeling

Self-optimizing control – A survey

Self-optimizing control is a strategy for selecting controlled variables. It is distinguished by the fact that an economic objective function is adopted as a selection criterion. The aim is to systematically select the controlled variables such that by controlling them at constant setpoints, the impact of uncertain and varying disturbances on the economic optimality is minimized. If a selection leads to an acceptable economic loss compared to perfectly optimal operation then the chosen control structure is referred to as “self-optimizing”. In this comprehensive survey on methods for finding self-optimizing controlled variables we summarize the progress made during the last fifteen years. In particular, we present brute-force methods, local methods based on linearization, data and regression based methods, and methods for finding nonlinear controlled variables for polynomial systems. We also discuss important related topics such as handling changing active constraints. Finally, we point out open problems and directions for future research

Cranial form evolution and functional adaptations to diet among papionins : a comparative study combining quantitative genetics, geometric morphometrics, and finite element analysis

This thesis aims to study the evolution of cranial form and its biomechanical adaptation to the function of feeding in papionins, a group of primates with well-established phylogeny, large variations in cranial form, and well known ecologies and diets. The thesis firstly tests the hypothesis of evolutionary divergence of papionin cranial forms by random genetic drift with a quantitative genetic model (previously tested for acceptable type I error rates); if rejected, different cranial forms should reflect adaptations to the particular biomechanical demands of different diets. To study those adaptations, hypotheses about the cranial biomechanical performance under biting loads are then formulated in terms of the diet of each papionin species and tested using 3D finite element models and geometric morphometrics. Large scale deformations and cranial form are assessed using landmarks distributed over the cranium, and local strain distributions are assessed visually. Lastly, the association between cranial form, biomechanical parameters and diet among papionin species is tested using partial least squares. Results show that papionin cranial forms did not diverge by random genetic drift alone and thus adaptation must have occurred. When testing for biomechanical adaptation to biting, there are differences in cranial deformations between durophagous and graminivorous species, each with particular adaptations in the cranium that are thus apparent in cranial strains and deformations. Another striking result is that male and female crania of a single species (eating the same foods) deform similarly, albeit having different forms. The cranium of the phylogenetic outgroup Macaca deforms differently from all other papionins, but generally cranial deformations do not follow the phylogenetic relationship among papionins. Finally, a statistically significant association is found between cranial form and cranial deformations, and between diet and cranial form. Bite force and deformations show a less clear association with diet