Academic literature on the topic 'Plant model with time delays'

Direct synthesis controller design approach has serious limitations when it is applied to plant models that have more complex models and models involving time delays. In such cases the design becomes more cumbersome and the time delay appears in the denominator making it difficult to realize. In order to get simple realizable controllers approximations of plant model and time delays are done. This leads to controllers with non-optimal parameters. In this paper, a new approach for designing the controller by combining direct synthesis approach and system identification is presented. The controller is identified from the plant model and the desired closed-loop without the need for approximating the plant model and the time delay and ensures that the controller parameters are optimal.

The joint parameter and time-delay estimation problems for a class of nonlinear multirate time-delay system with uncertain output delays are addressed in this paper. The practical process typically has time-delay properties and the process data are often multirate, sampled with output data inevitably corrupted by uncertain delays. The linear parameter varying (LPV) finite impulse response (FIR) multirate time-delay model is initially built to describe the considered system. The problems of over-parameterization and the existence of both continuous model parameters and discrete time-delays have made the conventional maximum likelihood difficult to solve the considered problems. In order to handle these problems, the joint parameter and time-delay estimation for the LPV FIR multirate time-delay model are formulated in the expectation-maximization scheme, and the algorithm to estimate the model parameters and time-delays is derived, simultaneously based on multirate process data. The efficacy of the proposed method is verified through a numerical simulation and a practical chemical plant.

The paper deals with the model-based estimation of hormone concentrations that are inaccessible for direct measurement in the blood stream. Previous research demonstrated that the dynamics of nonbasal endocrine regulation can be closely captured by linear continuous models with time delays under a pulse-modulated feedback. The presence of continuous time delays is inevitable in such a model due to transport phenomena and the time necessary for an endocrine gland to produce a certain hormone quantity. Yet, thanks to the finite-dimensional reducibility of the linear time-delay part of the system, a finite-dimensional model can be used to reconstruct both the continuous and discrete states of the hybrid time-delay plant. A hybrid observer exploiting this possibility is suggested and analyzed by means of a discrete impulse-to-impulse mapping.

This paper develops a new approach for the output model reference adaptive control of linear continuous-time plants with state delays. The main idea is to include into the control law a feedforward component that compensates for the delayed states, in addition to output feedback. The feedforward is formed by special adaptively adjusted prefilters as a function of the delayed state of the reference model. The output feedback component is designed as for a plant without delay, but applied to the time-delay plant. Such a controller structure containing adaptive output feedback and adaptive prefilters from the delayed reference model makes it possible to solve the problem of adaptive exact asymptotic output tracking under parametric uncertainties. The stability is analyzed using the Lyapunov-Krasovskii functional method. A simulated example illustrates the new controller.

Assessing productivity, cost, and delays are essential to manage any construction operation, particularly the concrete batch plant (CBP) operation. This paper focuses on assessing the above-mentioned items for the CBP using stochastic mathematical models. It aims at (i) identifying the potential sources of delay in the CBP operation; (ii) assessing their influence on production, efficiency, time, and cost; and (iii) determining each factor share in inflating the CBP concrete unit expense. Stochastic mathematical models were designed to accomplish the aforementioned objectives. Data were collected from five CBP sites in Indiana, USA, to implement and verify the designed models. Results show that delays due to management conditions have the highest probability of occurrence (0.43), expected value of delay percent (62.54% out of total delays), and relative delay percent. The expected value of efficiency for all plants is 86.53%; however, the average total expense is US$15.56/m3 (all currency are in US$). In addition, the expected value of effective expenses (EE) is $18.03/m3, resulting in extra expenses (XE) of $2.47/m3. This research is relevant to both industry practitioners and researchers. It develops models to determine the effect of delays on concrete unit cost. They are also beneficial to the CBP management.Key words: concrete batch plant, delays, management conditions, cost models, cost management, stochastic mathematical models.

Because of the interlinking of process equipments in process industry, event information may propagate through the plant and affect a lot of downstream process variables. Specifying the causality and estimating the time delays among process variables are critically important for data-driven fault prognosis. They are not only helpful to find the root cause when a plant-wide disturbance occurs, but to reveal the evolution of an abnormal event propagating through the plant. This paper concerns with the information flow directionality and time-delay estimation problems in process industry and presents an information synchronization technique to assist fault prognosis. Time-delayed mutual information (TDMI) is used for both causality analysis and time-delay estimation. To represent causality structure of high-dimensional process variables, a time-delayed signed digraph (TD-SDG) model is developed. Then, a general fault prognosis strategy is developed based on the TD-SDG model and principle component analysis (PCA). The proposed method is applied to an air separation unit and has achieved satisfying results in predicting the frequently occurred “nitrogen-block” fault.

Purpose The purpose of this paper is to concern the design of a robust model predictive controller for distributed networked systems with transmission delays. Design/methodology/approach The overall system is composed of a number of interconnected nonlinear subsystems with time-varying transmission delays. A distributed networked system with transmission delays is modeled as a nonlinear system with a time-varying delay. Time delays appear in distributed systems due to the information transmission in the communication network or transport of material between the sub-plants. In real applications, the states may not be available directly and it could be a challenge to address the control problem in interconnected systems using a centralized architecture because of the constraints on the computational capabilities and the communication bandwidth. The controller design is characterized as an optimization problem of a “worst-case” objective function over an infinite moving horizon. Findings The aim is to propose control synthesis approach that depends on nonlinearity and time varying delay characteristics. The MPC problem is represented in a time varying delayed state feedback structure. Then the synthesis sufficient condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time instant. In the rest, an LMI-based decentralized observer-based robust model predictive control strategy is proposed. Originality/value The authors develop RMPC strategies for a class of distributed networked systems with transmission delays using LMI-Based technique. To evaluate the applicability of the developed approach, the control design of a networked chemical reactor plant with two sub-plants is studied. The simulation results show the effectiveness of the proposed method.

In this paper, we propose a Model Predictive Controller (MPC) based on Gaussian process for nonlinear systems with uncertain delays and external Gaussian disturbances. We investigate the ability of Gaussian process based MPC on handling the variable delay that follows a Gaussian distribution through a properly selected observation horizon. To test the effectiveness of this approach, comparisons are made for the proposed Gaussian process based MPC and RBF (Radial Basis Function) neural networks by analyzing the time complexity and control performance. In simulations, two experiments are designed to verify the results of different systems, including a first-order nonlinear plant and a second-order nonlinear plant with variable delays and Gaussian noises. It is demonstrated that the proposed approach may achieve the desired results.

Abstract Despite the fact that punctuality is an advantage of rail travel compared with other long-distance transport, train delays often occur. For this study, a three-month dataset of weather, train delay and train schedule records was collected and analysed in order to understand the patterns of train delays and to predict train delay time. We found that in severe weather train delays are determined mainly by the type of bad weather, while in ordinary weather the delays are determined mainly by the historical delay time and delay frequency of trains. Identifying the factors closely correlated with train delays, we developed a machine-learning model to predict the delay time of each train at each station. The prediction model is useful not only for passengers wishing to plan their journeys more reliably, but also for railway operators developing more efficient train schedules and more reasonable pricing plans.

This thesis deals with model predictive control principally Based Predictive Control (MPC). The first part describes the principle of predictive control, cost function, the choice of a constraints in regulation and the choice of weights. In the next section is an analysis system: a system with non-minimal phase (control water turbine), oscillating systems (trolley frame control) and system with a time-delay . In all of these systems is performed classical feedback control using PID control and concurrently regulation with the MPC. MPC is selected as the solution fy Mathworks Model Predictive Control Toolbox and Simulink. The results are then analyzed using the criteria of quality control.

The chemical processes used to manufacture pulp are always in development to cope with increasing environmental demands and competition. With a deeper understanding of the processes, the pulping industry can become both more profitable and effective at keeping an even and good quality of pulp, while reducing emissions. One step in this direction is to more accurately determine the time delay for a process, defined as the time it takes for a change in input to affect the process’s output. This information can then be used to control the process more efficiently. The methods used today to estimate the time delay use simple models and assumptions of the processes, for example that that the pulp behaves like a ”plug” that never changes its shape throughout the process. The problem with these assumptions is that they are only valid under ideal circumstances where there are no disturbances. This Master’s thesis aims to investigate if it is possible to measure the process time delay using only the input and output data from the process, and see if this estimation is more accurate than the existing model based methods. Another aim is to investigate if the process time delay can be monitored in real time. We investigated three methods: cross-correlation applied to the raw input and output data, cross-correlation applied to the derivative of the input and output data, and a convolutional neural network trained to identify the process time delay from the input and output data. The results show that it is possible to find the time delay, but with significant deviations from the models used today. Due to a lack of data where the time delay was measured, the reason for this deviation requires more research. The results also show that the three methods are unsuitable for real-time estimation. However, the models can likely monitor how the process time delay develops over long periods.

El alto grado de automatización adquirido en las plantas químicas durante las últimas décadas hace que las tareas de supervisión sean ahora más complejas y delicadas. Esta supervisión requiere de sistemas y herramientas sofisticadas que puedan sacar provecho de los módulos de adquisición de información instalados en planta. Así, el preciso seguimiento de las variables de proceso o la fácil operatividad de los procesos, gracias a los sistemas de control regulatorio actuales, son aspectos relevantes que deben ser contemplados a la hora de dar una respuesta global a las desviaciones del régimen normal de operación.
Esta tesis presenta un enfoque global para la gestión de situaciones anormales en plantas químicas. En esta propuesta se contempla el flujo completo de información requerido para responder efectivamente a cualquier situación anormal que se pueda presentar. Mediante esta visión global, primeramente se identifican todos los módulos de planta involucrados en la gestión de fallos; luego se focalizan esfuerzos en mejorar las técnicas que estos módulos usan para su operación; por último, se aprovechan algunas de las sinergias descubiertas mediante esta visión global de la gestión de eventos anormales.
De esta forma, el primer capítulo esetablece un primer acercamiento general a las motivaciones y ámbito de las tesis, describiendo rasgos fundamentales en la evolución de la industria química durante los últimos años y los requerimientos asociados al nuevo modelo de supervisión. El segundo capítulo resume las técnicas y aplicaciones actuales para reducir el riesgo de incidencias y accidentes en procesos químicos. Este resumen se centra principalmente en aquellas metodologías más empleadas en la literatura y aquellas con más aceptación en ambientes industriales. Una vez analizado el estado del arte en la supervisión de procesos, se propone un enfoque global de gestión de eventos anormales en el tercer capítulo, que presenta los eslabones de la cadena de gestión de eventos anormales, los cuales serán abordados en detalle en los capítulos restantes.
De esta forma, el capítulo 4 se centra en la mejora de los sistemas de adquisición de datos y su posterior tratamiento mediante reconciliación con modelos del proceso. Los capítulos 5, 6, 7 y 8 se dedican al estudio de la parte central de cualquier sistema de respuesta a eventos anormales, el módulo de diagnóstico. El capítulo 5 formaliza el problema de diagnosis y estandariza los índices de evaluación de funcionamiento de los sistemas de diagnóstico. Los capítulo 6 y 7 preentan dos nuevos sistemas de diagnosis basados en el uso de datos históricos. El primero desarrollado en el capítulo 6, implementa un algoritmo de aprendizaje llamada "Máquinas de soporte vectorial" (SVM) adoptando un enfoque "MultiEtiqueta" que permite el diagnóstico eficaz de fallos simultáneos. El segundo sistema (capítulo 7) integra un módulo de detección basado en un modelo de Análisis de Componentes Principales y un módulo de diagnóstico basado en reglas "si-entonces". Como compendio de la diagnosis, el capítulo 8 estudia las fuerzas y debilidades de los sistemas de diagnóstico propuestos y propone una integración de módulos de diagnóstico complementarios que supera el rendimiento de cualquiera de los sistemas por separado.
Los capítulos 9 y 10 están centrados en la toma efectiva de decisiones frente a desviaciones del régimen normal de operación. El capítulo 9 presenta una metodología novedosa de integración de conocimiento del proceso en línea y fuera de línea, que permite generar información sustancial de soporte al operador en la toma de decisiones. El capítulo 10 se centra también en la toma de decisiones, mostrando las sinergias generadas al integrar el sistema de diagnosis con otros módulos de planta. En este capítulo el sistema global de gestión de eventos anormales es complementado con un módulo de optimización en línea. De esta forma el nuevo soporte a la toma de decisiones frente a perturbaciones no sólo tiene en cuenta aspectos relacionados con la seguridad sino también con la economía de la planta. Además, la integración permite que la técnica de optimizaicón empleada sea más fiable en su aplicación.
Todos los capítulos incluyen una primera parte teórica seguida de una segunda parte centrada en la validación académica e industrail. Aquellos temas que exceden el alcance de estas tesis, son comentados y propuestos como trabajo futuro en el capítulo 11.
The hight automation acquired in chemical industry during last decades has made supervision a delicate and complex task. Therefore, current plants supervision require of sophisticated systems and tools that can create profit from the information installed modules. Thus, the precise tracking of process variables or the high plant operability, achieved by the current regulatory control, are aspects that must be contemplated when the plant has to give a global response against deviations from normal operating regime.
This thesis presents a global approach for the management of abnormal situations in chemical plants. In this proposal the complete flow of information required to respond to any nonstandard situation is considered. This global approach incorporates several key aspects: first, all the plant modules that are necessary in the faults management are presented; secondly, this thesis focuses on improving the techniques used in each of these modules so far. Lastly, synergies discovered by the proposed global approach are used to develop novel and promising solutions to address process safety and optimization difficulties.

A prominent feature of the dynamics of large neuronal networks are the synchrony-driven collective oscillations generated by the interplay between synaptic coupling and synaptic delays. This thesis investigates the emergence of delay-induced oscillations in networks of heterogeneous spiking neurons. Building on recent theoretical advances in exact mean field reductions for neuronal networks, this work explores the dynamics and bifurcations of an exact firing rate model with various forms of synaptic delays. In parallel, the results obtained using the novel firing rate model are compared with extensive numerical simulations of large networks of spiking neurons, which confirm the existence of numerous synchrony-based oscillatory states. Some of these states are novel and display complex forms of partial synchronization and collective chaos. Given the well-known limitation of traditional firing rate models to describe synchrony-based oscillations, previous studies greatly overlooked many of the oscillatory states found here. Therefore, this thesis provides a unique exploration of the oscillatory scenarios found in neuronal networks due to the presence of delays, and may substantially extend the mathematical tools available for modeling the plethora of oscillations detected in electrical recordings of brain activity.
Una característica fonamental de la dinàmica d'una xarxa neuronal és l'emergència d'oscil·lacions degudes a sincronització. L'origen d'aquestes oscil·lacions és molt sovint degut les interaccions sinàptiques i als seus retards temporals inherents. Aquesta tesi analitza la emergència d'oscil·lacions produïdes per retards sinàptics en xarxes neuronals heterogènies. A partir de troballes recents en teories de camp mig per xarxes neuronals, aquest treball explora la dinàmica i les bifurcacions d'un model de {\it rate} amb diferents tipus de retards sinàptics. En paral·lel els resultats obtinguts mitjançant el nou model de rate són comparats amb simulacions numèriques de grans xarxes neuronals. Aquestes simulacions confirmen l'existència de nombrosos estats oscil·latoris produïts per sincronització. Alguns d'aquests estats són nous I mostren formes complexes de sincronització parcial i de caos col·lectiu. Gran part d'aquestes oscil·lacions han estat àmpliament ignorades a la literatura, degut a la limitació dels models tradicionals de rate per descriure estats amb un alt nivell de sincronització. Així doncs aquesta tesi ofereix una exploració única dels possibles escenaris oscil·latoris en xarxes neuronals amb retards sinàptics, i amplia significativament les eines matemàtiques disponibles per a la modelització de la gran diversitat d'oscil·lacions neuronals presents en les mesures elèctriques de l'activitat cerebral.

Ecologists traditionally regard time as part of the background against which ecological interactions play out. This book argues that time should be treated as a resource used by organisms for growth, maintenance, and offspring production. The book uses insights from phenology—the study of the timing of life-cycle events—to present a theoretical framework of time in ecology that casts long-standing observations in the field in an entirely new light. Combining conceptual models with field data, the book demonstrates how phenological advances, delays, and stasis, documented in an array of taxa, can all be viewed as adaptive components of an organism's strategic use of time. The book shows how the allocation of time by individual organisms to critical life history stages is not only a response to environmental cues but also an important driver of interactions at the population, species, and community levels. To demonstrate the applications of this exciting new conceptual framework, the book uses meta-analyses of previous studies as well as the author's original data on the phenological dynamics of plants, caribou, and muskoxen in Greenland.

This article discusses the results of a study in Bayesian analysis and decision making in the maintenance and reliability of nuclear power plants. It demonstrates the use of Bayesian parametric and semiparametric methodology to analyse the failure times of components that belong to an auxiliary feedwater system in a nuclear power plant at the South Texas Project (STP) Electric Generation Station. The parametric models produce estimates of the hazard functions that are compared to the output from a mixture of Polya trees model. The statistical output is used as the most critical input in a stochastic optimization model which finds the optimal replacement time for a system that randomly fails over a finite horizon. The article first introduces the model for maintenance and reliability analysis before presenting the optimization results. It also examines the nuclear power plant data to be used in the Bayesian models.

This chapter addresses the analysis and quantification of electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Topics include characteristics of these signals and practical issues such as sampling, filtering, and artifact rejection. Basic concepts of analysis in time and frequency domains are presented, with attention to non-stationary signals focusing on time-frequency signal decomposition, analytic signal and Hilbert transform, wavelet transform, matching pursuit, blind source separation and independent component analysis, canonical correlation analysis, and empirical model decomposition. The behavior of these methods in denoising EEG signals is illustrated. Concepts of functional and effective connectivity are developed with emphasis on methods to estimate causality and phase and time delays using linear and nonlinear methods. Attention is given to Granger causality and methods inspired by this concept. A concrete example is provided to show how information processing methods can be combined in the detection and classification of transient events in EEG/MEG signals.

Nationalism: Past as Prologue began as a single volume being compiled by Ad Akande, a scholar from South Africa, who proposed it to me as co-author about two years ago. The original idea was to examine how the damaging roots of nationalism have been corroding political systems around the world, and creating dangerous obstacles for necessary international cooperation. Since I (Bruce E. Johansen) has written profusely about climate change (global warming, a.k.a. infrared forcing), I suggested a concerted effort in that direction. This is a worldwide existential threat that affects every living thing on Earth. It often compounds upon itself, so delays in reducing emissions of fossil fuels are shortening the amount of time remaining to eliminate the use of fossil fuels to preserve a livable planet. Nationalism often impedes solutions to this problem (among many others), as nations place their singular needs above the common good. Our initial proposal got around, and abstracts on many subjects arrived. Within a few weeks, we had enough good material for a 100,000-word book. The book then fattened to two moderate volumes and then to four two very hefty tomes. We tried several different titles as good submissions swelled. We also discovered that our best contributors were experts in their fields, which ranged the world. We settled on three stand-alone books:” 1/ nationalism and racial justice. Our first volume grew as the growth of Black Lives Matter following the brutal killing of George Floyd ignited protests over police brutality and other issues during 2020, following the police assassination of Floyd in Minneapolis. It is estimated that more people took part in protests of police brutality during the summer of 2020 than any other series of marches in United States history. This includes upheavals during the 1960s over racial issues and against the war in Southeast Asia (notably Vietnam). We choose a volume on racism because it is one of nationalism’s main motive forces. This volume provides a worldwide array of work on nationalism’s growth in various countries, usually by authors residing in them, or in the United States with ethnic ties to the nation being examined, often recent immigrants to the United States from them. Our roster of contributors comprises a small United Nations of insightful, well-written research and commentary from Indonesia, New Zealand, Australia, China, India, South Africa, France, Portugal, Estonia, Hungary, Russia, Poland, Kazakhstan, Georgia, and the United States. Volume 2 (this one) describes and analyzes nationalism, by country, around the world, except for the United States; and 3/material directly related to President Donald Trump, and the United States. The first volume is under consideration at the Texas A & M University Press. The other two are under contract to Nova Science Publishers (which includes social sciences). These three volumes may be used individually or as a set. Environmental material is taken up in appropriate places in each of the three books. * * * * * What became the United States of America has been strongly nationalist since the English of present-day Massachusetts and Jamestown first hit North America’s eastern shores. The country propelled itself across North America with the self-serving ideology of “manifest destiny” for four centuries before Donald Trump came along. Anyone who believes that a Trumpian affection for deportation of “illegals” is a new thing ought to take a look at immigration and deportation statistics in Adam Goodman’s The Deportation Machine: America’s Long History of Deporting Immigrants (Princeton University Press, 2020). Between 1920 and 2018, the United States deported 56.3 million people, compared with 51.7 million who were granted legal immigration status during the same dates. Nearly nine of ten deportees were Mexican (Nolan, 2020, 83). This kind of nationalism, has become an assassin of democracy as well as an impediment to solving global problems. Paul Krugman wrote in the New York Times (2019:A-25): that “In their 2018 book, How Democracies Die, the political scientists Steven Levitsky and Daniel Ziblatt documented how this process has played out in many countries, from Vladimir Putin’s Russia, to Recep Erdogan’s Turkey, to Viktor Orban’s Hungary. Add to these India’s Narendra Modi, China’s Xi Jinping, and the United States’ Donald Trump, among others. Bit by bit, the guardrails of democracy have been torn down, as institutions meant to serve the public became tools of ruling parties and self-serving ideologies, weaponized to punish and intimidate opposition parties’ opponents. On paper, these countries are still democracies; in practice, they have become one-party regimes….And it’s happening here [the United States] as we speak. If you are not worried about the future of American democracy, you aren’t paying attention” (Krugmam, 2019, A-25). We are reminded continuously that the late Carl Sagan, one of our most insightful scientific public intellectuals, had an interesting theory about highly developed civilizations. Given the number of stars and planets that must exist in the vast reaches of the universe, he said, there must be other highly developed and organized forms of life. Distance may keep us from making physical contact, but Sagan said that another reason we may never be on speaking terms with another intelligent race is (judging from our own example) could be their penchant for destroying themselves in relatively short order after reaching technological complexity. This book’s chapters, introduction, and conclusion examine the worldwide rise of partisan nationalism and the damage it has wrought on the worldwide pursuit of solutions for issues requiring worldwide scope, such scientific co-operation public health and others, mixing analysis of both. We use both historical description and analysis. This analysis concludes with a description of why we must avoid the isolating nature of nationalism that isolates people and encourages separation if we are to deal with issues of world-wide concern, and to maintain a sustainable, survivable Earth, placing the dominant political movement of our time against the Earth’s existential crises. Our contributors, all experts in their fields, each have assumed responsibility for a country, or two if they are related. This work entwines themes of worldwide concern with the political growth of nationalism because leaders with such a worldview are disinclined to co-operate internationally at a time when nations must find ways to solve common problems, such as the climate crisis. Inability to cooperate at this stage may doom everyone, eventually, to an overheated, stormy future plagued by droughts and deluges portending shortages of food and other essential commodities, meanwhile destroying large coastal urban areas because of rising sea levels. Future historians may look back at our time and wonder why as well as how our world succumbed to isolating nationalism at a time when time was so short for cooperative intervention which is crucial for survival of a sustainable earth. Pride in language and culture is salubrious to individuals’ sense of history and identity. Excess nationalism that prevents international co-operation on harmful worldwide maladies is quite another. As Pope Francis has pointed out: For all of our connectivity due to expansion of social media, ability to communicate can breed contempt as well as mutual trust. “For all our hyper-connectivity,” said Francis, “We witnessed a fragmentation that made it more difficult to resolve problems that affect us all” (Horowitz, 2020, A-12). The pope’s encyclical, titled “Brothers All,” also said: “The forces of myopic, extremist, resentful, and aggressive nationalism are on the rise.” The pope’s document also advocates support for migrants, as well as resistance to nationalist and tribal populism. Francis broadened his critique to the role of market capitalism, as well as nationalism has failed the peoples of the world when they need co-operation and solidarity in the face of the world-wide corona virus pandemic. Humankind needs to unite into “a new sense of the human family [Fratelli Tutti, “Brothers All”], that rejects war at all costs” (Pope, 2020, 6-A). Our journey takes us first to Russia, with the able eye and honed expertise of Richard D. Anderson, Jr. who teaches as UCLA and publishes on the subject of his chapter: “Putin, Russian identity, and Russia’s conduct at home and abroad.” Readers should find Dr. Anderson’s analysis fascinating because Vladimir Putin, the singular leader of Russian foreign and domestic policy these days (and perhaps for the rest of his life, given how malleable Russia’s Constitution has become) may be a short man physically, but has high ambitions. One of these involves restoring the old Russian (and Soviet) empire, which would involve re-subjugating a number of nations that broke off as the old order dissolved about 30 years ago. President (shall we say czar?) Putin also has international ambitions, notably by destabilizing the United States, where election meddling has become a specialty. The sight of Putin and U.S. president Donald Trump, two very rich men (Putin $70-$200 billion; Trump $2.5 billion), nuzzling in friendship would probably set Thomas Jefferson and Vladimir Lenin spinning in their graves. The road of history can take some unanticipated twists and turns. Consider Poland, from which we have an expert native analysis in chapter 2, Bartosz Hlebowicz, who is a Polish anthropologist and journalist. His piece is titled “Lawless and Unjust: How to Quickly Make Your Own Country a Puppet State Run by a Group of Hoodlums – the Hopeless Case of Poland (2015–2020).” When I visited Poland to teach and lecture twice between 2006 and 2008, most people seemed to be walking on air induced by freedom to conduct their own affairs to an unusual degree for a state usually squeezed between nationalists in Germany and Russia. What did the Poles then do in a couple of decades? Read Hlebowicz’ chapter and decide. It certainly isn’t soft-bellied liberalism. In Chapter 3, with Bruce E. Johansen, we visit China’s western provinces, the lands of Tibet as well as the Uighurs and other Muslims in the Xinjiang region, who would most assuredly resent being characterized as being possessed by the Chinese of the Han to the east. As a student of Native American history, I had never before thought of the Tibetans and Uighurs as Native peoples struggling against the Independence-minded peoples of a land that is called an adjunct of China on most of our maps. The random act of sitting next to a young woman on an Air India flight out of Hyderabad, bound for New Delhi taught me that the Tibetans had something to share with the Lakota, the Iroquois, and hundreds of other Native American states and nations in North America. Active resistance to Chinese rule lasted into the mid-nineteenth century, and continues today in a subversive manner, even in song, as I learned in 2018 when I acted as a foreign adjudicator on a Ph.D. dissertation by a Tibetan student at the University of Madras (in what is now in a city called Chennai), in southwestern India on resistance in song during Tibet’s recent history. Tibet is one of very few places on Earth where a young dissident can get shot to death for singing a song that troubles China’s Quest for Lebensraum. The situation in Xinjiang region, where close to a million Muslims have been interned in “reeducation” camps surrounded with brick walls and barbed wire. They sing, too. Come with us and hear the music. Back to Europe now, in Chapter 4, to Portugal and Spain, we find a break in the general pattern of nationalism. Portugal has been more progressive governmentally than most. Spain varies from a liberal majority to military coups, a pattern which has been exported to Latin America. A situation such as this can make use of the term “populism” problematic, because general usage in our time usually ties the word into a right-wing connotative straightjacket. “Populism” can be used to describe progressive (left-wing) insurgencies as well. José Pinto, who is native to Portugal and also researches and writes in Spanish as well as English, in “Populism in Portugal and Spain: a Real Neighbourhood?” provides insight into these historical paradoxes. Hungary shares some historical inclinations with Poland (above). Both emerged from Soviet dominance in an air of developing freedom and multicultural diversity after the Berlin Wall fell and the Soviet Union collapsed. Then, gradually at first, right wing-forces began to tighten up, stripping structures supporting popular freedom, from the courts, mass media, and other institutions. In Chapter 5, Bernard Tamas, in “From Youth Movement to Right-Liberal Wing Authoritarianism: The Rise of Fidesz and the Decline of Hungarian Democracy” puts the renewed growth of political and social repression into a context of worldwide nationalism. Tamas, an associate professor of political science at Valdosta State University, has been a postdoctoral fellow at Harvard University and a Fulbright scholar at the Central European University in Budapest, Hungary. His books include From Dissident to Party Politics: The Struggle for Democracy in Post-Communist Hungary (2007). Bear in mind that not everyone shares Orbán’s vision of what will make this nation great, again. On graffiti-covered walls in Budapest, Runes (traditional Hungarian script) has been found that read “Orbán is a motherfucker” (Mikanowski, 2019, 58). Also in Europe, in Chapter 6, Professor Ronan Le Coadic, of the University of Rennes, Rennes, France, in “Is There a Revival of French Nationalism?” Stating this title in the form of a question is quite appropriate because France’s nationalistic shift has built and ebbed several times during the last few decades. For a time after 2000, it came close to assuming the role of a substantial minority, only to ebb after that. In 2017, the candidate of the National Front reached the second round of the French presidential election. This was the second time this nationalist party reached the second round of the presidential election in the history of the Fifth Republic. In 2002, however, Jean-Marie Le Pen had only obtained 17.79% of the votes, while fifteen years later his daughter, Marine Le Pen, almost doubled her father's record, reaching 33.90% of the votes cast. Moreover, in the 2019 European elections, re-named Rassemblement National obtained the largest number of votes of all French political formations and can therefore boast of being "the leading party in France.” The brutality of oppressive nationalism may be expressed in personal relationships, such as child abuse. While Indonesia and Aotearoa [the Maoris’ name for New Zealand] hold very different ranks in the United Nations Human Development Programme assessments, where Indonesia is classified as a medium development country and Aotearoa New Zealand as a very high development country. In Chapter 7, “Domestic Violence Against Women in Indonesia and Aotearoa New Zealand: Making Sense of Differences and Similarities” co-authors, in Chapter 8, Mandy Morgan and Dr. Elli N. Hayati, from New Zealand and Indonesia respectively, found that despite their socio-economic differences, one in three women in each country experience physical or sexual intimate partner violence over their lifetime. In this chapter ther authors aim to deepen understandings of domestic violence through discussion of the socio-economic and demographic characteristics of theit countries to address domestic violence alongside studies of women’s attitudes to gender norms and experiences of intimate partner violence. One of the most surprising and upsetting scholarly journeys that a North American student may take involves Adolf Hitler’s comments on oppression of American Indians and Blacks as he imagined the construction of the Nazi state, a genesis of nationalism that is all but unknown in the United States of America, traced in this volume (Chapter 8) by co-editor Johansen. Beginning in Mein Kampf, during the 1920s, Hitler explicitly used the westward expansion of the United States across North America as a model and justification for Nazi conquest and anticipated colonization by Germans of what the Nazis called the “wild East” – the Slavic nations of Poland, the Baltic states, Ukraine, and Russia, most of which were under control of the Soviet Union. The Volga River (in Russia) was styled by Hitler as the Germans’ Mississippi, and covered wagons were readied for the German “manifest destiny” of imprisoning, eradicating, and replacing peoples the Nazis deemed inferior, all with direct references to events in North America during the previous century. At the same time, with no sense of contradiction, the Nazis partook of a long-standing German romanticism of Native Americans. One of Goebbels’ less propitious schemes was to confer honorary Aryan status on Native American tribes, in the hope that they would rise up against their oppressors. U.S. racial attitudes were “evidence [to the Nazis] that America was evolving in the right direction, despite its specious rhetoric about equality.” Ming Xie, originally from Beijing, in the People’s Republic of China, in Chapter 9, “News Coverage and Public Perceptions of the Social Credit System in China,” writes that The State Council of China in 2014 announced “that a nationwide social credit system would be established” in China. “Under this system, individuals, private companies, social organizations, and governmental agencies are assigned a score which will be calculated based on their trustworthiness and daily actions such as transaction history, professional conduct, obedience to law, corruption, tax evasion, and academic plagiarism.” The “nationalism” in this case is that of the state over the individual. China has 1.4 billion people; this system takes their measure for the purpose of state control. Once fully operational, control will be more subtle. People who are subject to it, through modern technology (most often smart phones) will prompt many people to self-censor. Orwell, modernized, might write: “Your smart phone is watching you.” Ming Xie holds two Ph.Ds, one in Public Administration from University of Nebraska at Omaha and another in Cultural Anthropology from the Chinese Academy of Social Sciences, Beijing, where she also worked for more than 10 years at a national think tank in the same institution. While there she summarized news from non-Chinese sources for senior members of the Chinese Communist Party. Ming is presently an assistant professor at the Department of Political Science and Criminal Justice, West Texas A&M University. In Chapter 10, analyzing native peoples and nationhood, Barbara Alice Mann, Professor of Honours at the University of Toledo, in “Divide, et Impera: The Self-Genocide Game” details ways in which European-American invaders deprive the conquered of their sense of nationhood as part of a subjugation system that amounts to genocide, rubbing out their languages and cultures -- and ultimately forcing the native peoples to assimilate on their own, for survival in a culture that is foreign to them. Mann is one of Native American Studies’ most acute critics of conquests’ contradictions, and an author who retrieves Native history with a powerful sense of voice and purpose, having authored roughly a dozen books and numerous book chapters, among many other works, who has traveled around the world lecturing and publishing on many subjects. Nalanda Roy and S. Mae Pedron in Chapter 11, “Understanding the Face of Humanity: The Rohingya Genocide.” describe one of the largest forced migrations in the history of the human race, the removal of 700,000 to 800,000 Muslims from Buddhist Myanmar to Bangladesh, which itself is already one of the most crowded and impoverished nations on Earth. With about 150 million people packed into an area the size of Nebraska and Iowa (population less than a tenth that of Bangladesh, a country that is losing land steadily to rising sea levels and erosion of the Ganges river delta. The Rohingyas’ refugee camp has been squeezed onto a gigantic, eroding, muddy slope that contains nearly no vegetation. However, Bangladesh is majority Muslim, so while the Rohingya may starve, they won’t be shot to death by marauding armies. Both authors of this exquisite (and excruciating) account teach at Georgia Southern University in Savannah, Georgia, Roy as an associate professor of International Studies and Asian politics, and Pedron as a graduate student; Roy originally hails from very eastern India, close to both Myanmar and Bangladesh, so he has special insight into the context of one of the most brutal genocides of our time, or any other. This is our case describing the problems that nationalism has and will pose for the sustainability of the Earth as our little blue-and-green orb becomes more crowded over time. The old ways, in which national arguments often end in devastating wars, are obsolete, given that the Earth and all the people, plants, and other animals that it sustains are faced with the existential threat of a climate crisis that within two centuries, more or less, will flood large parts of coastal cities, and endanger many species of plants and animals. To survive, we must listen to the Earth, and observe her travails, because they are increasingly our own.

Phenomenological models mathematically describe relationships among empirically observed phenomena without attempting to explain underlying mechanisms. Within the context of NLTS, phenomenological modeling goes beyond phase space reconstruction to extract equations governing real-world system dynamics from a single or multiple observed time series. Phenomenological models provide several benefits. They can be used to characterize the dynamics of variable interactions; for example, whether an incremental increase in one variable drives a marginal increase/decrease in the growth rate of another, and whether these dynamic interactions follow systematic patterns over time. They provide an analytical framework for data driven science still searching for credible theoretical explanation. They set a descriptive standard for how the real world operates so that theory is not misdirected in explaining fanciful behavior. The success of phenomenological modeling depends critically on selection of governing parameters. Model dimensionality, and the time delays used to synthesize dynamic variables, are guided by statistical tests run for phase space reconstruction. Other regression and numerical integration parameters can be set on a trial and error basis within ranges providing numerical stability and successful reproduction of empirically-detected dynamics. We illustrate phenomenological modeling with solutions of the Lorenz model so that we can recognize the dynamics that need to be reproduced.

AbstractTwo chassis components were developed at the Technische Universität Darmstadt that are used to isolate the body and to reduce wheel load fluctuation.The frequency responses of the components were identified with a stochastic foot point excitation in a hardware-in-the-loop (HiL) simulation environment at the hydropulser. The modelling of the transmission behaviour influence of the testing machine on the frequency response was approximately represented with a time delay of $$10\,\mathrm {ms}$$ 10 ms in the frequency range up to $$25\,\mathrm {Hz}$$ 25 Hz . This is considered by a Padé approximation. It can be seen that the dynamics of the testing machine have an influence on the wheel load fluctuation and the body acceleration, especially in the natural frequency of the unsprung mass. Therefor, the HiL stability is analysed by mapping the poles of the system in the complex plane, influenced by the time delay and virtual damping.This paper presents the transfer from virtual to real quarter car to quantify the model uncertainty of the component, since the time delay impact does not occur in the real quarter car test rig. The base point excitation directly is provided by the testing machine and not like in the case of the HiL test rig, the compression of the spring damper calculated in the real-time simulation.

Investigation on using network for distributed systems is an important topic in the motion control industry. This paper presents solutions to time-delay and packet-loss problems encountered in distributed real-time operation of an open-loop unstable magnetic levitation (maglev) test bed via an Ethernet. A novel model predictive control strategy with optimal controller design is developed to overcome the adverse influences of time delays and packet losses. By using the prediction of system states and the event-driven and time-driven smart actuator simultaneously, the plant receives the current control signal in every sampling interval even at the presence of time delays and packet losses. Thus we can compensate the time-delay and packet-loss in a uniform way. The simulation and experimental results demonstrated the feasibility and effectiveness of this control algorithm for NCSs with long stochastic time delays and successive packet losses.

In this paper, we develop a sliding mode model reference adaptive control (MRAC) scheme for a class of nonlinear dynamic systems with multiple time-varying state delays which is robust with respect to unknown plant delays, to a nonlinear perturbation, and to an external disturbance with unknown bounds. An appropriate Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms, and to prove stability.

The performance of a 300 kW Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) pilot power plant simulator is evaluated by applying a set of robust Proportional Integral Derivative (PID) controllers that satisfy time delay and gain uncertainties of the SOFC-GT system. The actuators are a fuel valve (FV) that models the fuel cell thermal exhaust, and a cold-air (CA) valve which bypasses airflow rate from the fuel cell cathode. The robust PID controller results for the uncertain gains are presented first, followed by a design for uncertain time delays for both, FV and CA bypass valves. The final design incorporates the combined uncertain gain parameters with the time delay modeling of both actuators. This Multiple-Input Multiple-Output (MIMO) technique is beneficial to plants having a wide range of operation and a strong parameter interaction. The practical implementation is presented through simulation in the Matlab/Simulink environment.

Concept of the real-time hybrid model (ReaTHM® 2) testing framework for marine hybrid power plant is presented. The benefits and challenges with regard to using the model-scale power plant for the testing are explained. As a feasibility study of the methodology, tests are performed at the Hybrid Power Laboratory with a model-scale physical diesel-electric power plant. In this test, a load profile from onboard measurements from a ship is used as a numerical part of the system. In the model-scale power plant, the electrical part of the plant is used as an actuator to generate the load for the diesel engine. The traceability of the components and the total system to the given load profile is quantified in terms of time delay and tracking errors. For conclusion, the limitation of the test is analyzed and suggestions for improving the results are provided.

Input shaper is a pre-filter, designed to suppress residual vibration of flexible systems. The input shaper can be placed inside the feedback loop, in front of the flexible plant, to avoid exciting the plant vibratory modes. The performance of this so-called closed-loop signal shaping is limited due to the time delay brought about by the input shaper. The input shaper has more time delay when the plant mode parameters are uncertain. In this paper, an inner-loop controller based on the quantitative feedback theory is designed to match the uncertain flexible plant to a reference model. As a result, the input shaper needs not be robust, and the time delay is reduced. Other benefits include shorter input shaper length, increasing controller bandwidth, applicable to time-varying plant, and reducing cost of feedback. Simulation and experiment have confirmed the effectiveness of the newly proposed technique.

Abstract Human balancing on rolling balance board in the sagittal plane is analyzed such that the geometry of the balance board can be adjusted: the radius R of the wheels and the elevation h between the top of the wheels and the board can be changed. These two parameters have a significant influence on the stability of standing on the board as shown by preliminary experiments. The human body was modeled by a single inverted pendulum, while the balance board was considered by the geometry of the mechanical model. Based on literature, it was assumed that the central nervous system (CNS) controls by signals proportional to the angle and angular velocity of the human body and the balance board and is able to tune the feedback gains with 40% accuracy during the balancing process. To take the reaction time into consideration, operation of the CNS was modeled as a delayed proportional-derivative feedback. The critical time delay for the stabilization process is defined such that if the delay is larger than the critical one then no control gains could stabilize the system. Four balance board configurations were chosen with different wheel radius and the corresponding critical time delays were computed based on the mechanical model. Eight young healthy individuals participated in the experiments. Their task was to perform 60 s long balancing trials on each balance board. The reaction time of the participants was estimated by comparing the numerical results obtained for the critical time delay and their successful and unsuccessful balancing trials. The reaction times were found to be in the range of 0.10–0.15 s which are in good agreement with the literature.

Delays in supply chains due to decision making (of managers) and lead time (in production) cause undesirable effects to inventory levels. Via system’s thinking, key mechanisms leading to such effects are investigated by analyzing the stability of an inventory, departing from a commonly studied model. On this model, two distinct delays and a PI controller to remove offset in inventory, are incorporated. On the plane of delays, stable and unstable operational behavior of inventory level are identified on so-called stability maps. Next, effects of PI controller to stability are revealed and this controller is optimized for avoiding oscillatory nature of inventory level. Case studies are provided to demonstrate counter-intuitive effects of delay presence to supply chain management and how stability maps may serve as decision-making tools for managers in achieving better control on inventory behavior.

A method of noncollocated controller design for non-uniform flexible structures, governed by the wave equation, is proposed. An exact, infinite dimensional, transfer function, relating the actuation and measurement points, with general boundary conditions, is derived for the multi-link case. Three modeling methods are presented and discussed. A key element of the model is the existence of time delays, due to the wave motion, which play a major role in the controller design. The design consists of two stages. First an inner rate loop is closed in order to improve the system dynamic behavior. It leads to a finite dimensional plus delay inner closed loop, which is the equivalent plant for the outer loop. In the second stage an outer noncollocated position loop is closed. It has the structure of an observer–predictor control scheme to compensate for the response delay. The resulting overall transfer function is second order, with arbitrarily assigned dynamics, plus delay.

The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.