Several methods are presented for the design of satellite formations for science missions in high-eccentricity reference orbits with quantifiable performance criteria specified throughout only a portion the orbit, called the Region of Interest (RoI). A modified form of the traditional average along-track drift minimization condition is introduced to account for the fact that performance criteria are only specified within the RoI, and a robust formation design algorithm (FDA) is defined to improve performance in the presence of formation initialization errors. Initial differential mean orbital elements are taken as the design variables and the Gim-Alfriend state transition matrix (G-A STM) is used for relative motion propagation. Using mean elements and the G-A STM allows for explicit inclusion of J2 perturbation effects in the design process. The methods are applied to the complete formation design problem of the NASA Magnetospheric Multiscale (MMS) mission and results are verified using the NASA General Mission Analysis Tool (GMAT). Since satellite formations in high-eccentricity orbits will spend long times at high altitude, third-body perturbations are an important design consideration as well. A detailed analytical analysis of third-body perturbation effects on satellite formations is also performed and averaged dynamics are derived for the particular case of the lunar perturbation. Numerical results of the lunar perturbation analysis are obtained for the example application of the MMS mission and verified in GMAT.

Digital image watermarking has gained a great interest in the last decade among researchers. Having such a great community which provide a continuously growing list of proposed algorithms, it is rapidly finding solutions to its problems. However, still we are far away from being successful. Therefore, more and more people are entering the field to make the watermarking idea useful and reliable for digital world. Of these various watermarking algorithms, some outperform others in terms of basic watermarking requirements like robustness, invisibility, processing cost, etc. In this thesis, we study the performances of different watermarking algorithms in terms of robustness. Algorithms are chosen to be representatives of different categories such as spatial and transform domain. We evaluate the performance of a selected set of 9 different methods from the watermarking literature against again a selected set of attacks and distortions and try to figure out the properties of the methods that make them vulnerable or invulnerable against these attacks.

The design of optimal strictly positive real (SPR) compensators using numerical optimization is considered. The plants to be controlled are linear and nonlinear flexible manipulators. For the design of SISO and MIMO linear SPR controllers, the optimization objective function is defined by reformulating the H2-optimal control problem subject to the constraint that the controllers must be SPR. Various controller parameterizations using transfer functions/matrices and state-space equations are considered. Depending on the controller form, constraints are enforced (i) using simple inequalities guaranteeing SPRness, (ii) in the frequency domain, or (iii) by implementing the Kalman-Yakubovich- Popov lemma. The design of a gain-scheduled SPR controller using numerical optimization is also considered. Using a family of linear SPR controllers, the time dependent scheduling signals are parameterized, and the objective function of the optimizer seeks to find the form of the scheduling signals which minimizes the manipulator tip tracking error while minimizing the control effort.

This dissertation studies interference in wireless networks. Interference results from multiple simultaneous attempts to communicate, often between unassociated sources and receivers, preventing extensive coordination. Moreover, in practical wireless networks, learning network state is inherently expensive, and nodes often have incomplete and mismatched views of the network. The fundamental communication limits of a network with such views is unknown. To address this, we present a local view model which captures asymmetries in node knowledge. Our local view model does not rely on accurate knowledge of an underlying probability distribution governing network state. Therefore, we can make robust statements about the fundamental limits of communication when the channel is quasi-static or the actual distribution of state is unknown: commonly faced scenarios in modern commercial networks. For each local view, channel state parameters are either perfectly known or completely unknown. While we propose no mechanism for network learning, a local view represents the result of some such mechanism. We apply the local view model to study the two-user Gaussian interference channel: the smallest building block of any interference network. All seven possible local views are studied, and we find that for five of the seven, there exists no policy or protocol that universally outperforms time-division multiplexing (TDM), justifying the orthogonalized approach of many deployed systems. For two of the seven views, TDM-beating performance is possible with use of opportunistic schemes where opportunities are revealed by the local view. We then study how message cooperation --- either at transmitters or receivers --- increases capacity in the local view two-user Gaussian interference channel. The cooperative setup is particularly appropriate for modeling next-generation cellular networks, where costs to share message data among base stations is low relative to costs to learn channel coefficients. For the cooperative setting, we find: (1) opportunistic approaches are still needed to outperform TDM, but (2) opportunities are more abundant and revealed by more local views. For all cases studied, we characterize the capacity region to within some known gap, enabling computation of the generalized degrees of freedom region, a visualization of spatial channel resource usage efficiency.

Continuous scaling of the transistor size and reduction of the operating voltage have led to a significant performance improvement of integrated circuits. However, the vulnerability of the scaled circuits to transient data upsets or soft errors, which are caused by alpha particles and cosmic neutrons, has emerged as a major reliability concern. In this thesis, we have investigated the effects of soft errors in combinational circuits and proposed soft error detection techniques for high speed adders. In particular, we have proposed an area-efficient 64-bit soft error robust logarithmic adder (SRA). The adder employs the carry merge Sklansky adder architecture in which carries are generated every 4 bits. Since the particle-induced transient, which is often referred to as a single event transient (SET) typically lasts for 100~200 ps, the adder uses time redundancy by sampling the sum outputs twice. The sampling instances have been set at 110 ps apart. In contrast to the traditional time redundancy, which requires two clock cycles to generate a given output, the SRA generates an output in a single clock cycle. The sampled sum outputs are compared using a 64-bit XOR tree to detect any possible error. An energy efficient 4-input transmission gate based XOR logic is implemented to reduce the delay and the power in this case. The pseudo-static logic (PSL), which has the ability to recover from a particle induced transient, is used in the adder implementation. In comparison with the space redundant approach which requires hardware duplication for error detection, the SRA is 50% more area efficient. The proposed SRA is simulated for different operands with errors inserted at different nodes at the inputs, the carry merge tree, and the sum generation circuit. The simulation vectors are carefully chosen such that the SET is not masked by error masking mechanisms, which are inherently present in combinational circuits. Simulation results show that the proposed SRA is capable of detecting 77% of the errors. The undetected errors primarily result when the SET causes an even number of errors and when errors occur outside the sampling window.

In deregulated electricity markets, generating companies submit energy bids which are derived from a self-schedule. In this thesis, we propose an improved semidefinite programming-based model for the self-scheduling problem. The model provides the profit-maximizing generation quantities of a single generator over a multi-period horizon and accounts for uncertainty in prices using robust optimization. Within this robust framework, the price information is represented analytically as an ellipsoid. The risk-adversity of the decision maker is taken into account by a scaling parameter. Hence, the focus of the model is directed toward the trade-off between profit and risk. The bounds obtained by the proposed approach are shown to be significantly better than those obtained by a mean-variance approach from the literature. We then apply the proposed model within a branch-and-bound algorithm to improve the quality of the solutions. The resulting solutions are also compared with the mean-variance approach, which is formulated as a mixed-integer quadratic programming problem. The results indicate that the proposed approach produces solutions which are closer to integrality and have lower relative error than the mean-variance approach.

Observers are used in the monitoring and control of dynamical systems to deduce the values of unmeasured states. Designing an observer requires having an accurate model of the plant — if the model parameters are characterized imprecisely, the observer may not provide reliable estimates. An interval observer, which comprises an upper and lower observer, bounds the plant's states from above and below, given the range of values of the imprecisely characterized parameters, i.e., it defines an interval in which the plant's states must lie at any given instant. We propose a linear programming-based method of interval observer design for two cases: 1) only the initial conditions of the plant are uncertain; 2) the dynamical parameters are also uncertain. In the former, we optimize the transient performance of the interval observers, in the sense that the volume enclosed by the interval is minimized. In the latter, we optimize the steady state performance of the interval observers, in the sense that the norm of the width of the interval is minimized at steady state. Interval observers are typically designed to characterize the widest interval that bounds the states. This thesis proposes an interval observer design method that utilizes additional, but still-incomplete information, that enables the designer to identify tighter bounds on the uncertain parameters under certain operating conditions. The number of bounds that can be refined defines a class of systems. The definition of this class is independent of the specific parameters whose bounds are refined. Applying robust optimization techniques, under a cardinality constrained model of uncertainty, we design a single observer for an entire class of systems. These observers guarantee a minimum level of performance with respect to the aforementioned metrics, as we optimize the worst-case performance over a given class of systems. The robust formulation allows the designer to tune the level of uncertainty in the model. If many of the uncertain parameter bounds can be refined, the nominal performance of the observer can be improved, however, if few or none of the parameter bounds can be refined, the nominal performance of the observer can be designed to be more conservative.

Robust control design has become a major research area during the last twenty years and there are nowadays several robust design methods available. One example of such a method is the robust loop shaping method that was developed by K. Glover and D. C. MacFarlane in the late 1980s. The idea of this method is to use decentralized controller design to give the singular values of the loop gain a desired shape. This step is called Loop Shaping and it is followed by a Robust Stabilization procedure, which aims to give the closed loop system a maximum degree of stability margins. In this thesis, the robust loop shaping method is used to design a gain scheduled controller for a missile. The report consists of three parts, where the first part introduces the Robust Loop Shaping theory and a Gain Scheduling approach. The second part discusses the missile and its characteristics. In the third part a controller is designed and a short analysis of the closed loop system is performed. A scheduled controller is implemented in a nonlinear environment, in which performance and robustness are tested. Robust Loop Shaping is easy to use and simulations show that the resulting controller is able to cope with model perturbations without considerable loss in performance. The missile should be able to operate in a large speed interval. There, it is shown that a single controller does not stabilize the missile everywhere. The gain scheduled controller is however able to do so, which is shown by means of simulations.

This thesis has been performed at SAAB Bofors Dynamics. The purpose was to derive a robust control design for a nonlinear missile using backstepping. A particularly interesting matter was to see how different design choices affect the robustness. Backstepping is a relatively new design method for nonlinear systems which leads to globally stabilizing control laws. By making wise decisions in the design the resulting closed loop can receive significant robustness. The method also makes it possible to benefit from naturally stabilizing aerodynamic forces and momentums. It is based on Lyapunov theory and the control laws and a Lyapunov function are derived simultaneously. This Lyapunov function is used to guarantee stability. In this thesis the control laws for the missile are first derived by using backstepping. The missile dynamics are described with aerodynamic coeffcients with corresponding uncertainties. The robustness of the design w.r.t. the aerodynamic uncertainties is then studied further in detail. One way to analyze how the stability is affected by the errors in the coeffcients is presented. To improve the robustness and remove static errors, dynamics are introduced in the control laws by adding an integrator. One conclusion that has been reached is that it is hard to immediately determine how a certain design choice affects the robustness. Instead it is at the point when algebraic expressions for the closed loop system have been obtained, that it is possible to analyze the affects of a certain design choice. The designed control laws are evaluated by simulations which shows satisfactory results.

Scania has a policy to attain a high crashworthiness standard and their trucks have to conform to Swedish cab safety standards. The main objective of this thesis is to clarify which parameter variations, present during the second part of the Swedish cab crashworthiness test on a Scania R-series cab, that have significance on the intrusion response. An LS-DYNA FE-model of the test case is analysed where parameter variations are introduced through the use of the probabilistic analysis tool LS-OPT. Example of analysed variations are the sheet thickness variation as well as the material variations such as stress-strain curve of the structural components, but also variations in the test setup such as the pendulum velocity and angle of approach on impact are taken into account. The effect of including the component forming in the analysis is investigated, where the variations on the material parameters are implemented prior to the forming. An additional objective is to analyse the influence of simulation and model dependent variations and weigh their respective effect on intrusion with the above stated physical variations. A submodel is created due to the necessity to speed up the simulations since the numerous parameter variations yield a large number of different designs, resulting in multiple analyses. Important structural component sensitivities are taken from the results and should be used as a pointer where to focus the attention when trying to increase the robustness of the cab. Also, the results show that the placement of the pendulum in the y direction (sideways seen from the driver perspective) is the most significant physical parameter variation during the Swedish pendulum test. It is concluded that to be able to achieve a fair comparison of the structural performance from repeated crash testing, this pendulum variation must be kept to a minimum. Simulation and model dependent parameters in general showed to have large effects on the intrusion. It is concluded that further investigations on individual simulation or model dependent parameters should be performed to establish which description to use. Mapping material effects from the forming simulation into the crash model gave a slight stiffer response compared to the mean pre-stretch approximations currently used by Scania. This is still however a significant result considering that Scanias approximations also included bake hardening effects from the painting process.