Design, specification, and synthesis of aircraft electric power systems control logic

Cyber-physical systems integrate computation, networking, and physical processes. Substantial research challenges exist in the design and verification of such large-scale, distributed sensing, ac- tuation, and control systems. Rapidly improving technology and recent advances in control theory, networked systems, and computer science give us the opportunity to drastically improve our approach to integrated flow of information and cooperative behavior. Current systems rely on text-based spec- ifications and manual design. Using new technology advances, we can create easier, more efficient, and cheaper ways of developing these control systems. This thesis will focus on design considera- tions for system topologies, ways to formally and automatically specify requirements, and methods to synthesize reactive control protocols, all within the context of an aircraft electric power system as a representative application area.

This thesis consists of three complementary parts: synthesis, specification, and design. The first section focuses on the synthesis of central and distributed reactive controllers for an aircraft elec- tric power system. This approach incorporates methodologies from computer science and control. The resulting controllers are correct by construction with respect to system requirements, which are formulated using the specification language of linear temporal logic (LTL). The second section addresses how to formally specify requirements and introduces a domain-specific language for electric power systems. A software tool automatically converts high-level requirements into LTL and synthesizes a controller.

The final sections focus on design space exploration. A design methodology is proposed that uses mixed-integer linear programming to obtain candidate topologies, which are then used to synthesize controllers. The discrete-time control logic is then verified in real-time by two methods: hardware and simulation. Finally, the problem of partial observability and dynamic state estimation is ex- plored. Given a set placement of sensors on an electric power system, measurements from these sensors can be used in conjunction with control logic to infer the state of the system.

Microstructure control and iodine doping of bismuth telluride

On the materials scale, thermoelectric efficiency is defined by the dimensionless figure of merit zT. This value is made up of three material components in the form zT = Tα²/ρκ, where α is the Seebeck coefficient, ρ is the electrical resistivity, and κ is the total thermal conductivity. Therefore, in order to improve zT would require the reduction of κ and ρ while increasing α. However due to the inter-relation of the electrical and thermal properties of materials, typical routes to thermoelectric enhancement come in one of two forms. The first is to isolate the electronic properties and increase α without negatively affecting ρ. Techniques like electron filtering, quantum confinement, and density of states distortions have been proposed to enhance the Seebeck coefficient in thermoelectric materials. However, it has been difficult to prove the efficacy of these techniques. More recently efforts to manipulate the band degeneracy in semiconductors has been explored as a means to enhance α.

The other route to thermoelectric enhancement is through minimizing the thermal conductivity, κ. More specifically, thermal conductivity can be broken into two parts, an electronic and lattice term, κ_e and κ_l respectively. From a functional materials standpoint, the reduction in lattice thermal conductivity should have a minimal effect on the electronic properties. Most routes incorporate techniques that focus on the reduction of the lattice thermal conductivity. The components that make up κ_l (κ_l = 1/3Cνl) are the heat capacity (C), phonon group velocity (ν), and phonon mean free path (l). Since the difficulty is extreme in altering the heat capacity and group velocity, the phonon mean free path is most often the source of reduction.

Past routes to decreasing the phonon mean free path has been by alloying and grain size reduction. However, in these techniques the electron mobility is often negatively affected because in alloying any perturbation to the periodic potential can cause additional adverse carrier scattering. Grain size reduction has been another successful route to enhancing zT because of the significant difference in electron and phonon mean free paths. However, grain size reduction is erratic in anisotropic materials due to the orientation dependent transport properties. However, microstructure formation in both equilibrium and nonequilibrium processing routines can be used to effectively reduce the phonon mean free path as a route to enhance the figure of merit.

This work starts with a discussion of several different deliberate microstructure varieties. Control of the morphology and finally structure size and spacing is discussed at length. Since the material example used throughout this thesis is anisotropic a short primer on zone melting is presented as an effective route to growing homogeneous and oriented polycrystalline material. The resulting microstructure formation and control is presented specifically in the case of In₂Te₃-Bi₂Te₃ composites and the transport properties pertinent to thermoelectric materials is presented. Finally, the transport and discussion of iodine doped Bi₂Te₃ is presented as a re-evaluation of the literature data and what is known today.

Distributed Control and Optimization for Communication and Power Systems

We are at the cusp of a historic transformation of both communication system and electricity system. This creates challenges as well as opportunities for the study of networked systems. Problems of these systems typically involve a huge number of end points that require intelligent coordination in a distributed manner. In this thesis, we develop models, theories, and scalable distributed optimization and control algorithms to overcome these challenges.

This thesis focuses on two specific areas: multi-path TCP (Transmission Control Protocol) and electricity distribution system operation and control. Multi-path TCP (MP-TCP) is a TCP extension that allows a single data stream to be split across multiple paths. MP-TCP has the potential to greatly improve reliability as well as efficiency of communication devices. We propose a fluid model for a large class of MP-TCP algorithms and identify design criteria that guarantee the existence, uniqueness, and stability of system equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss the implications of these properties on the behavior of existing algorithms and motivate a new algorithm Balia (balanced linked adaptation) which generalizes existing algorithms and strikes a good balance among TCP-friendliness, responsiveness, and window oscillation. We have implemented Balia in the Linux kernel. We use our prototype to compare the new proposed algorithm Balia with existing MP-TCP algorithms.

Our second focus is on designing computationally efficient algorithms for electricity distribution system operation and control. First, we develop efficient algorithms for feeder reconfiguration in distribution networks. The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed integer nonlinear program and hence hard to solve. We propose a heuristic algorithm that is based on the recently developed convex relaxation of the optimal power flow problem. The algorithm is efficient and can successfully computes an optimal configuration on all networks that we have tested. Moreover we prove that the algorithm solves the feeder reconfiguration problem optimally under certain conditions. We also propose a more efficient algorithm and it incurs a loss in optimality of less than 3% on the test networks.

Second, we develop efficient distributed algorithms that solve the optimal power flow (OPF) problem on distribution networks. The OPF problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally OPF is solved in a centralized manner. With increasing penetration of volatile renewable energy resources in distribution systems, we need faster and distributed solutions for real-time feedback control. This is difficult because power flow equations are nonlinear and kirchhoff's law is global. We propose solutions for both balanced and unbalanced radial distribution networks. They exploit recent results that suggest solving for a globally optimal solution of OPF over a radial network through a second-order cone program (SOCP) or semi-definite program (SDP) relaxation. Our distributed algorithms are based on the alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative methods, the proposed solutions exploit the problem structure that greatly reduce the computation time. Specifically, for balanced networks, our decomposition allows us to derive closed form solutions for these subproblems and it speeds up the convergence by 1000x times in simulations. For unbalanced networks, the subproblems reduce to either closed form solutions or eigenvalue problems whose size remains constant as the network scales up and computation time is reduced by 100x compared with iterative methods.

Management of broodstock and quality control of fish seed in Hungary

Common carp (Cyprinus carpio) breeding has a long tradition in Hungary. However, recent economic changes in Eastern Europe and new developments in aquaculture necessitated the need for ensuring quality of the brood stock used in hatcheries and the legal and institutional frameworks needed to implement the program. In addition to good research and development programs and gene banking, it became essential to establish an appropriate legal framework, organize, coordinate and control breeding activities, and provide financial support. It was a major breakthrough for carp breeding when C.carpio was recognized as one of the cultivated animals in the Animal Breeding Act in 1993. The Carp Breeding Section of the Hungarian Fish Producers Association plays an important role in carp breeding programs. Thirteen breeding farms of the Carp Breeding Section have 24 certified C.carpio varieties. In Hungary, about 80 % of the seed used as stocking for commercial production are from high quality certified breeders.

Adaptive agent-based manufacturing control and its application to flow shop routing control

The manufacturing industry is currently facing unprecedented challenges from changes and disturbances. The sources of these changes and disturbances are of different scope and magnitude. They can be of a commercial nature, or linked to fast product development and design, or purely operational (e.g. rush order, machine breakdown, material shortage etc.). In order to meet these requirements it is increasingly important that a production operation be flexible and is able to adapt to new and more suitable ways of operating. This paper focuses on a new strategy for enabling manufacturing control systems to adapt to changing conditions both in terms of product variation and production system upgrades. The approach proposed is based on two key concepts: (1) An autonomous and distributed approach to manufacturing control based on multi-agent methods in which so called operational agents represent the key physical and logical elements in the production environment to be controlled - for example, products and machines and the control strategies that drive them and (2) An adaptation mechanism based around the evolutionary concept of replicator dynamics which updates the behaviour of newly formed operational agents based on historical performance records in order to be better suited to the production environment. An application of this approach for route selection of similar products in manufacturing flow shops is developed and is illustrated in this paper using an example based on the control of an automobile paint shop.

Modelling and predictive control: Enabling technologies for reconfiguration

An approach to reconfiguring control systems in the event of major failures is advocated. The approach relies on the convergence of several technologies which are currently emerging: Constrained predictive control, High-fidelity modelling of complex systems, Fault detection and identification, and Model approximation and simplification. Much work is needed, both theoretical and algorithmic, to make this approach practical, but we believe that there is enough evidence, especially from existing industrial practice, for the scheme to be considered realistic. After outlining the problem and proposed solution, the paper briefly reviews constrained predictive control and object-oriented modelling, which are the essential ingredients for practical implementation. The prospects for automatic model simplification are also reviewed briefly. The paper emphasizes some emerging trends in industrial practice, especially as regards modelling and control of complex systems. Examples from process control and flight control are used to illustrate some of the ideas.