Robust Control of Evolutionary Dynamics

The application of principles from evolutionary biology has long been used to gain new insights into the progression and clinical control of both infectious diseases and neoplasms. This iterative evolutionary process consists of expansion, diversification and selection within an adaptive landscape - species are subject to random genetic or epigenetic alterations that result in variations; genetic information is inherited through asexual reproduction and strong selective pressures such as therapeutic intervention can lead to the adaptation and expansion of resistant variants. These principles lie at the center of modern evolutionary synthesis and constitute the primary reasons for the development of resistance and therapeutic failure, but also provide a framework that allows for more effective control.

A model system for studying the evolution of resistance and control of therapeutic failure is the treatment of chronic HIV-1 infection by broadly neutralizing antibody (bNAb) therapy. A relatively recent discovery is that a minority of HIV-infected individuals can produce broadly neutralizing antibodies, that is, antibodies that inhibit infection by many strains of HIV. Passive transfer of human antibodies for the prevention and treatment of HIV-1 infection is increasingly being considered as an alternative to a conventional vaccine. However, recent evolution studies have uncovered that antibody treatment can exert selective pressure on virus that results in the rapid evolution of resistance. In certain cases, complete resistance to an antibody is conferred with a single amino acid substitution on the viral envelope of HIV.

The challenges in uncovering resistance mechanisms and designing effective combination strategies to control evolutionary processes and prevent therapeutic failure apply more broadly. We are motivated by two questions: Can we predict the evolution to resistance by characterizing genetic alterations that contribute to modified phenotypic fitness? Given an evolutionary landscape and a set of candidate therapies, can we computationally synthesize treatment strategies that control evolution to resistance?

To address the first question, we propose a mathematical framework to reason about evolutionary dynamics of HIV from computationally derived Gibbs energy fitness landscapes -- expanding the theoretical concept of an evolutionary landscape originally conceived by Sewall Wright to a computable, quantifiable, multidimensional, structurally defined fitness surface upon which to study complex HIV evolutionary outcomes.

To design combination treatment strategies that control evolution to resistance, we propose a methodology that solves for optimal combinations and concentrations of candidate therapies, and allows for the ability to quantifiably explore tradeoffs in treatment design, such as limiting the number of candidate therapies in the combination, dosage constraints and robustness to error. Our algorithm is based on the application of recent results in optimal control to an HIV evolutionary dynamics model and is constructed from experimentally derived antibody resistant phenotypes and their single antibody pharmacodynamics. This method represents a first step towards integrating principled engineering techniques with an experimentally based mathematical model in the rational design of combination treatment strategies and offers predictive understanding of the effects of combination therapies of evolutionary dynamics and resistance of HIV. Preliminary in vitro studies suggest that the combination antibody therapies predicted by our algorithm can neutralize heterogeneous viral populations despite containing resistant mutations.

Optimization and Control of Power Flow in Distribution Networks

Climate change is arguably the most critical issue facing our generation and the next. As we move towards a sustainable future, the grid is rapidly evolving with the integration of more and more renewable energy resources and the emergence of electric vehicles. In particular, large scale adoption of residential and commercial solar photovoltaics (PV) plants is completely changing the traditional slowly-varying unidirectional power flow nature of distribution systems. High share of intermittent renewables pose several technical challenges, including voltage and frequency control. But along with these challenges, renewable generators also bring with them millions of new DC-AC inverter controllers each year. These fast power electronic devices can provide an unprecedented opportunity to increase energy efficiency and improve power quality, if combined with well-designed inverter control algorithms. The main goal of this dissertation is to develop scalable power flow optimization and control methods that achieve system-wide efficiency, reliability, and robustness for power distribution networks of future with high penetration of distributed inverter-based renewable generators.

Proposed solutions to power flow control problems in the literature range from fully centralized to fully local ones. In this thesis, we will focus on the two ends of this spectrum. In the first half of this thesis (chapters 2 and 3), we seek optimal solutions to voltage control problems provided a centralized architecture with complete information. These solutions are particularly important for better understanding the overall system behavior and can serve as a benchmark to compare the performance of other control methods against. To this end, we first propose a branch flow model (BFM) for the analysis and optimization of radial and meshed networks. This model leads to a new approach to solve optimal power flow (OPF) problems using a two step relaxation procedure, which has proven to be both reliable and computationally efficient in dealing with the non-convexity of power flow equations in radial and weakly-meshed distribution networks. We will then apply the results to fast time- scale inverter var control problem and evaluate the performance on real-world circuits in Southern California Edison’s service territory.

The second half (chapters 4 and 5), however, is dedicated to study local control approaches, as they are the only options available for immediate implementation on today’s distribution networks that lack sufficient monitoring and communication infrastructure. In particular, we will follow a reverse and forward engineering approach to study the recently proposed piecewise linear volt/var control curves. It is the aim of this dissertation to tackle some key problems in these two areas and contribute by providing rigorous theoretical basis for future work.

Pollution and water quality control of the River Tejo. Report on a visit to Portugal, Sep 27th - October 10th, 1987

Fundamental changes in the management of water resources in Portugal are now evolving. Five regional organisations termed Administracaos de Regiao Hidrographic (ARH), will be created to manage water resources within their respective geographical areas. These areas will be catchment based. As a fore-runner to the implementation of the five ARH's a foundation project has been established within the Direcao-Geral do Recursos Naturais to examine the practical implications of the new system. This project has been divided into a number of sub-projects and complementary projects to include the Tejo complementary project. The Tejo complementary project is the focus of this report. The report is to advise on the role of biology in the proposed ARH, to establish priorities for biological studies within the present Projecto de Gestao Integrada dos Recursos Hidricos da Bacia Hidrografica do Rio Tejo (PGIRH/T) and to assist with the planning of laboratory facilities for biology at the new PGIRH/T laboratory at Alges, Lisboa.

Hydrobiological service for observations and control of surface waters in the USSR

Technological progress, having reached in our time an unprecedented speed, is still increasing the rate of mineral extraction, industrial construction, and the mastering of new kinds of energy is growing. Correspondingly the anthropogenic load on the biosphere is increased and that requires the comprehensive development of monitoring the anthropogenic changes in the natural environment. Among problems resulting from the scientific-technological development, a noticeable place is given to the problem of pure water. Surface land waters proved to be a sensitive link in the natural environment. The hydrobiological service for observations and control of the surface waters is one of the subsystems of the State/Federal Service for Observations and Control of pollution levels in environmental objects, conducted by the USSR State Committee for Hydrometeor- ology and Control of the Natural Environment. This paper summarises the the main principles of the organisation and goals of the national system of monitoring of the state of the natural environment in the USSR.

Control of polarization signal distortion by frequency domain phase conjugation in optical fiber systems

Optical frequency domain phase conjugation (FDPC) is based on phase conjugation of spectrum of an input signal. It is equivalent to the phase conjugation and the time reversal of the temporal envelope of an input signal. The use of FDPC to control polarization signal distortion in birefringent optical fiber systems is proposed. Evolution of polarization signals in the system using midway FDPC is analyzed theoretically and simulated numerically. It is shown that the distortion of polarization signals can be controlled effectively by FDPC. The impairments due to dispersion and nonlinear effects can be suppressed simultaneously.

Distributed Optimal Control of Cyber-Physical Systems: Controller Synthesis, Architecture Design and System Identification

The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.

The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.

We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.

Stabilization of optical Fabry-Perot sensor by active feedback control of diode laser

This paper presents the design and characterization of a fiber Fabry-Perot interferometer (FFPI) acoustic wave detector with its Q point being stabilized actively. The relationship between the reflectivity of the F-P cavity facets and cavity length was theoretically analyzed, and high visibility of 100% was realized by optimized design of the F-P cavity. To prevent the drifting of the Q point, a new stabilization method by actively feedback controlling of the diode laser is proposed and demonstrated, indicating the method is simple and easy operating. Measurement shows that good tracing of Q point was effectively realized. (c) 2008 Elsevier B.V. All rights reserved.

The control of indirect effects of biomanipulation

Results from long-term investigations on biomanipulation show that indirect effects are at least as important as direct effects are for the stability of biomanipulation. Three types of indirect effects can be distinguished: (1) a change in quantity or quality of the resource base, (2) behavioural change of the prey, and (3) development of anti-predator traits. Although indirect effects of type (2), (e.g. a change in the pattern of vertical migration of zooplankton), and type (3), (e.g. development of helmets and neck teeth in Daphnia), are important mechanisms, the most essential indirect effects regarding biomanipulation belong to type (1). An example of the latter will be demonstrated: the complex of indirect effects of enhanced grazing by large herbivores on the phosphorus metabolism of the lake. It is concluded that control of the indirect effects is absolutely necessary to stabilize biomanipulation measures, but this is much more difficult than the control of direct effects and needs deeper insights into the structuring mechanisms of food webs. Proper management of fish stocks, in combination with the control of phosphorus load and/or the physical conditions, seems to be the most promising way of controlling the indirect effects of biomanipulation.

A control of gas-vacuolate cyanobacteria

The cyanobacteria that cause problems in water supply are principally the colonial forms that are buoyed up by gas vesicles. The success of these organisms is due, in part, to their gas vesicles, which enable them to perform vertical migrations or to maintain themselves in the euphotic zone. The gas vesicles are also the root cause of the problems. In calm periods they cause the cyanobacteria to float to the water surface forming noxious scums, and they may prevent the colonies from sedimenting in water treatment plants. Gas vesicles are hollow, gas-filled structures; they are rigid but can be collapsed by the application of pressure. Their critical collapse pressure is influenced by their dimensions, which vary in different organisms. Gas vesicles are formed by the assembly of two types of protein, which determine their mechanical and physical properties. Methods for collapsing gas vesicles in natural populations of cyanobacteria will be considered. They may have application to the control of cyanobacteria in water supply.

Design and control of an ultraprecision stage used in grating tiling

In petawatt laser system, the gratings used to compose pulse compressor are very large in size which can be only acquired currently by arraying small aperture gratings to form a large one instead, an approach referred to as grating tiling. Theory and experiments have demonstrated that the coherent addition of multiple small gratings to form a larger grating is viable, the key technology of which is to control the relative position and orientation of each grating with high precision. According to the main factors that affect the performance of the grating tiling, a 5-DOF ultraprecision stage is developed for the grating tiling experiment. The mechanism is formed by serial structures. The motion of the mechanism is guided by flexure hinges and driven by piezoelectric actuators and the movement resolution of which can achieve nanometer level. To keep the stability of the mechanism, capacitive position sensors with nanometer accuracy are fixed on it to provide feedback signals with which to realize closed-loop control, thus the positioning precision of the mechanism is within several nanometers range through voltage control and digital PID algorithm. Results of experiments indicate that the performance of the mechanism can meet the requirement of precision for grating tiling.}