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.

Convex model predictive control for vehicular systems

In this work, the author presents a method called Convex Model Predictive Control (CMPC) to control systems whose states are elements of the rotation matrices SO(n) for n = 2, 3. This is done without charts or any local linearization, and instead is performed by operating over the orbitope of rotation matrices. This results in a novel model predictive control (MPC) scheme without the drawbacks associated with conventional linearization techniques such as slow computation time and local minima. Of particular emphasis is the application to aeronautical and vehicular systems, wherein the method removes many of the trigonometric terms associated with these systems’ state space equations. Furthermore, the method is shown to be compatible with many existing variants of MPC, including obstacle avoidance via Mixed Integer Linear Programming (MILP).

An economic air pollution control model-application : photochemical smog in Los Angeles County in 1975

An economic air pollution control model, which determines the least cost of reaching various air quality levels, is formulated. The model takes the form of a general, nonlinear, mathematical programming problem. Primary contaminant emission levels are the independent variables. The objective function is the cost of attaining various emission levels and is to be minimized subject to constraints that given air quality levels be attained.

The model is applied to a simplified statement of the photochemical smog problem in Los Angeles County in 1975 with emissions specified by a two-dimensional vector, total reactive hydrocarbon, (RHC), and nitrogen oxide, (NO_x), emissions. Air quality, also two-dimensional, is measured by the expected number of days per year that nitrogen dioxide, (NO₂), and mid-day ozone, (O₃), exceed standards in Central Los Angeles.

The minimum cost of reaching various emission levels is found by a linear programming model. The base or "uncontrolled" emission levels are those that will exist in 1975 with the present new car control program and with the degree of stationary source control existing in 1971. Controls, basically "add-on devices", are considered here for used cars, aircraft, and existing stationary sources. It is found that with these added controls, Los Angeles County emission levels [(1300 tons/day RHC, 1000 tons /day NO_x) in 1969] and [(670 tons/day RHC, 790 tons/day NO_x) at the base 1975 level], can be reduced to 260 tons/day RHC (minimum RHC program) and 460 tons/day NO_x (minimum NO_x program).

"Phenomenological" or statistical air quality models provide the relationship between air quality and emissions. These models estimate the relationship by using atmospheric monitoring data taken at one (yearly) emission level and by using certain simple physical assumptions, (e. g., that emissions are reduced proportionately at all points in space and time). For NO₂, (concentrations assumed proportional to NO_x emissions), it is found that standard violations in Central Los Angeles, (55 in 1969), can be reduced to 25, 5, and 0 days per year by controlling emissions to 800, 550, and 300 tons /day, respectively. A probabilistic model reveals that RHC control is much more effective than NO_x control in reducing Central Los Angeles ozone. The 150 days per year ozone violations in 1969 can be reduced to 75, 30, 10, and 0 days per year by abating RHC emissions to 700, 450, 300, and 150 tons/day, respectively, (at the 1969 NO_x emission level).

The control cost-emission level and air quality-emission level relationships are combined in a graphical solution of the complete model to find the cost of various air quality levels. Best possible air quality levels with the controls considered here are 8 O₃ and 10 NO₂ violations per year (minimum ozone program) or 25 O₃ and 3 NO₂ violations per year (minimum NO₂ program) with an annualized cost of $230,000,000 (above the estimated $150,000,000 per year for the new car control program for Los Angeles County motor vehicles in 1975).

Aplicación de la Programación lineal a la asignación de personal en un centro de llamadas

[ES] La necesidad de gestionar y repartir eficazmente los recursos escasos entre las diferentes operaciones de las empresas, hacen que éstas recurran a aplicar técnicas de la Investigación de Operaciones. Éste es el caso de los centros de llamadas, un sector emergente y dinámico que se encuentra en constante desarrollo. En este sector, la administración del trabajo requiere de técnicas predictivas para determinar el número de trabajadores adecuado y así evitar en la medida de lo posible tanto el exceso como la escasez del mismo. Este trabajo se centrará en el estudio del centro de llamadas de emergencias 112 de Andalucía. Partiendo de los datos estadísticos del número medio de llamadas que se realiza en cada franja horaria, facilitados por la Junta de esta Comunidad Autónoma, formularemos y modelizaremos el problema aplicando la Programación Lineal. Posteriormente, lo resolveremos con dos programas de software, con la finalidad de obtener una distribución óptima de agentes que minimice el coste salarial, ya que supone un 65% del gasto de explotación total. Finalmente, mediante la teoría de colas, observaremos los tiempos de espera en cola y calcularemos el número objetivo de agentes que permita no sólo minimizar el coste salarial sino mejorar la calidad de servicio teniendo unos tiempos de espera razonables.

Otimização da programação das limpezas em redes de trocadores de calor utilizando técnicas de programação matemática

Redes de trocadores de calor são bastante utilizadas na indústria química para promover a integração energética do processo, recuperando calor de correntes quentes para aquecer correntes frias. Estas redes estão sujeitas à deposição, o que causa um aumento na resistência à transferência de calor, prejudicando-a. Uma das principais formas de diminuir o prejuízo causado por este fenômeno é a realização periódica de limpezas nos trocadores de calor. O presente trabalho tem como objetivo desenvolver um novo método para encontrar a programação ótima das limpezas em uma rede de trocadores de calor. O método desenvolvido utiliza o conceito de horizonte deslizante associado a um problema de programação linear inteira mista (MILP). Este problema MILP é capaz de definir o conjunto ótimo de trocadores de calor a serem limpos em um determinado instante de tempo (primeiro instante do horizonte deslizante), levando em conta sua influência nos instantes futuros (restante do horizonte deslizante). O problema MILP utiliza restrições referentes aos balanços de energia, equações de trocadores de calor e número máximo de limpezas simultâneas, com o objetivo de minimizar o consumo de energia da planta. A programação ótima das limpezas é composta pela combinação dos resultados obtidos em cada um dos instantes de tempo.O desempenho desta abordagem foi analisado através de sua aplicação em diversos exemplos típicos apresentados na literatura, inclusive um exemplo de grande porte de uma refinaria brasileira. Os resultados mostraram que a abordagem aplicada foi capaz de prover ganhos semelhantes e, algumas vezes, superiores aos da literatura, indicando que o método desenvolvido é capaz de fornecer bons resultados com um baixo esforço computacional

Comparison of stochastic methods for control in air traffic management

This paper provides a direct comparison of two stochastic optimisation techniques (Markov Chain Monte Carlo and Sequential Monte Carlo) when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The two methods are then also compared to another existing technique of Mixed-Integer Linear Programming which is also popular in distributed control. © 2011 IFAC.

Continuous dynamical systems that realize discrete optimization on the hypercube

We study the problem of finding a local minimum of a multilinear function E over the discrete set {0,1}n. The search is achieved by a gradient-like system in [0,1]n with cost function E. Under mild restrictions on the metric, the stable attractors of the gradient-like system are shown to produce solutions of the problem, even when they are not in the vicinity of the discrete set {0,1}n. Moreover, the gradient-like system connects with interior point methods for linear programming and with the analog neural network studied by Vidyasagar (IEEE Trans. Automat. Control 40 (8) (1995) 1359), in the same context. © 2004 Elsevier B.V. All rights reserved.

Processing network models of energy/environment systems

Processing networks are a variant of the standard linear programming network model which are especially useful for optimizing industrial energy/environment systems. Modelling advantages include an intuitive diagrammatic representation and the ability to incorporate all forms of energy and pollutants in a single integrated linear network model. Added advantages include increased speed of solution and algorithms supporting formulation. The paper explores their use in modelling the energy and pollution control systems in large industrial plants. The pollution control options in an ethylene production plant are analyzed as an example. PROFLOW, a computer tool for the formulation, analysis, and solution of processing network models, is introduced.

a constraint solver and its application to path feasibility analysis

Many testing methods are based on program paths. A well-known problem with them is that some paths are infeasible. To decide the feasibility of paths, we may solve a set of constraints. In this paper, we describe constraint-based tools that can be used for this purpose. They accept constraints expressed in a natural form, which may involve variables of different types such as integers, Booleans, reals and fixed-size arrays. The constraint solver is an extension of a Boolean satisfiability checker and it makes use of a linear programming package. The solving algorithm is described, and examples are given to illustrate the use of the tools. For many paths in the testing literature, their feasibility can be decided in a reasonable amount of time.

Optimal design of a 7 T highly homogeneous superconducting magnet for a Penning trap

A Penning trap system called Lanzhou Penning Trap (LPT) is now being developed for precise mass measurements at the Institute of Modern Physics (IMP). One of the key components is a 7 T actively shielded superconducting magnet with a clear warm bore of 156 mm. The required field homogeneity is 3 x 10(-7) over two 1 cubic centimeter volumes lying 220 mm apart along the magnet axis. We introduce a two-step method which combines linear programming and a nonlinear optimization algorithm for designing the multi-section superconducting magnet. This method is fast and flexible for handling arbitrary shaped homogeneous volumes and coils. With the help of this method an optimal design for the LPT superconducting magnet has been obtained.

逆向物流流量不确定闭环供应链鲁棒运作策略设计

考虑一类同时具有再分销、再制造和再利用的闭环供应链在逆向物流流量不确定环境下的运作问题.采用具有已知概率的离散情景描述逆向物流流量的不确定性,利用基于情景分析的鲁棒线性优化方法建立该闭环供应链的多目标运作模型.设计了一个数值算例,其结果验证了运作策略的鲁棒性.在该算例基础上,分析了逆向物流流量的大小对闭环供应链系统运作性能的影响.

聚类引导搜索的移动机器人路径规划方法

本文提出一种聚类引导搜索（cluster guide searching，CGS）的路径规划方法。采用基于最大最小距离的K均值聚类方法对样本进行离线聚类学习，学习结果以相似环境相似决策的知识形式进行存储。路径规划过程中，机器人在线整理环境信息，获得输入空间样本，通过与知识库匹配，检索到最近的类别，然后在该类别内部采用速度优先策略和方向优先策略交替的方式搜索输出空间。若知识不完备导致检索失败，可重启线性规划算法（linear programming，LP）进行在线路径规划，并更新聚类知识库。仿真结果表明该方法是一种有效的路径规划学习方法。

任务分配问题的建模与求解

建立了极大极小任务分配问题的混合整数线性规划模型,提出一种矩阵作业解答,并与穷举解及混合整数线性规划解的计算复杂度进行了比较.理论分析和数值试验表明矩阵作业法对两类任务分配问题,极大极小和总体极小任务分配问题,有效地提供最优解.

加速度空间中基于线性规划的移动机器人路径规划方法

针对动态不确定环境下移动机器人的路径规划问题,提出了加速度空间中一种基于线性规划(Linear programming,LP)的方法.在机器人的加速度空间中利用相对信息,把机器人路径规划这一非线性问题,描述成满足一组线性约束同时使目标函数极小的线性规划问题,嵌入基于线性规划方法的规划器,得到一条满足性能要求的最优路径.仿真试验验证了算法的实用性及有效性,与势场引导进化计算的方法(Artificial potential guided evolution algorithm,APEA)相比更优化,更实时.

柔性制造系统的负荷分配及路径规划方法

柔性是柔性制造系统（ＦＭＳ）的一个基本优点，但这一基本优点却往往被人们所忽视，许多现在运行的ＦＭＳ不是缺乏柔性，就是没能充分利用可获得的柔性来提高生产效率柔性制造系统的负荷分配和路径规划问题正是这种柔性的一个主要方面．然而，路径规划决策却往往被忽视．其中一个主要原因就是人们仍不能从传统的生产管理概念中解放出来．本文在明确概念区分的基础上，提出了一种柔性制造系统的负荷分配和路径规划的线性规划模型，其主要特点是将负荷分配和路径规划问题有机地结合起来，并通过仿真实验验证并分析了此方法对ＦＭＳ性能上的影响。