Books on the topic 'Predictive motor control'

The monograph discusses the application of telematics in dispatch control systems in urban passenger transport. The role of telematics as a technological basis in automating the solution of control tasks, accounting and analysis of the volume and quality of transport work in modern dispatch control systems on urban passenger transport is shown. Analytical models have been developed to estimate the capacity of a high-speed bus transportation system on a dedicated line. Mathematical models and algorithms for predicting passenger vehicle interior filling at critical stages of urban passenger transport routes are presented. The issues of application of the concept of the phase space of states introduced by the authors to assess the quality of the passenger transportation process on the route of urban passenger transport are described. The developed classification of service levels and their application in order to inform passengers at stopping points about the degree of filling of the passenger compartment of the arriving vehicle is described. The material is based on the results of theoretical research and practical work on the creation and implementation of automated control systems for urban passenger transport in Russian cities. The material of M.H. Duque Sarango's dissertation submitted for the degree of Candidate of Technical Sciences in the specialty 05.22.10 "Operation of motor transport" was used. It will be useful to specialists in the field of telematics on urban passenger transport.

In this chapter, three control methods recently developed for or applied to electric motors in general and to permanent magnet synchronous (PMS) motors, in particular, are presented. The methods include model predictive control (MPC), deadbeat control (DBC), and combined vector and direct torque control (CC). The fundamental principles of the methods are explained, the machine models appropriate to the methods are derived, and the control systems are explained. The PMS motor performances under the control systems are also investigated. It is elaborated that MPC is capable of controlling the motor under an optimal performance according to a defined objective function. DBC, on the other hand, provides a very fast response in a single operating cycle. Finally, combined control produces motor dynamics faster than one under VC, with a smoother performance than the one under DTC.

This is the first comprehensive, coherent, and up-to-date book devoted solely to the control of permanent magnet synchronous (PMS) motors, as the fastest growing AC motor. It covers a deep and detailed presentation of major PMS motor modeling and control methods. The readers can find rich materials on the fundamentals of PMS motor control in addition to new motor control methods, which have mainly been developed in the last two decades, including recent advancements in the field in a systematic manner. These include extensive modeling of PMS motors and a full range of vector control and direct torque control schemes, in addition to predictive control, deadbeat control, and combined control methods. All major sensorless control and parameter estimation methods are also studied. The book covers about 10 machine models in various reference frames and 70 control and estimation schemes with sufficient analytical and implementation details including about 200 original figures. A great emphasis is placed on energy-saving control schemes. PMS motor performances under different control systems are presented by providing simulation and experimental results. The past, present, and future of the PMS motor market are also discussed. Each chapter concludes with end-chapter problems and focussed bibliographies. It is an essential source for anyone working on PMS motors in academic and industry sectors. The book can be used as a textbook with the first four chapters for a primary graduate course and the final three chapters for an advanced course. It is also a crucial reading for researchers, design engineers, and experts in the field.

An overview of permanent magnet synchronous (PMS) motors and the related control system are presented in this chapter as introductory materials for the rest of the book. The interconnections of the control system to the power electronic inverter and the motor are emphasized. In addition, the major parts of the system are overviewed. Pulse width-modulated voltage source inverter, as the most commonly used power converter in PMS motor drives, is briefly discussed. PMS motors configurations and operating principles are also presented after considering characteristics of permanent magnet materials. Major PMS motor control methods including vector control, direct torque control, predictive control, deadbeat control, and combined vector and direct torque control are briefly reviewed. Finally, several rotor position and speed estimation schemes, and offline and online parameter estimation methods are overviewed.

Over the last thirty years the comparator hypothesis has emerged as a prominent account of inner speech pathology. This chapter discusses a number of cognitive accounts broadly derived from this approach, highlighting the existence of two importantly distinct notions of inner speech in the literature; one as a prediction in the absence of sensory input, the other as an act with sensory consequences that are themselves predicted. Under earlier frameworks in which inner speech is described in the context of classic models of motor control, I argue that these two notions may be compatible, providing two routes to inner speech pathology. Under more recent accounts grounded in the architecture of Bayesian predictive processing, I argue that “active inference” approaches to action generation pose serious challenges to the plausibility of the latter notion of inner speech, while providing the former notion with rich explanatory possibilities for inner speech pathology.

The nature of inner language has long been under the scrutiny of humanities, through the practice of introspection. The use of experimental methods in cognitive neurosciences provides complementary insights. This chapter focuses on wilful expanded inner language, bearing in mind that other forms coexist. It first considers the abstract vs. concrete (or embodied) dimensions of inner language. In a second section, it argues that inner language should be considered as an action-perception phenomenon. In a third section, it proposes a revision of the “predictive control” account, fitting with our sensory-motor view. Inner language is considered as deriving from multisensory goals, generating multimodal acts (inner phonation, articulation, sign) with multisensory percepts (in the mind’s ear, tact, and eye). In the final section, it presents a landscape of the cerebral substrates of wilful inner verbalization, including multisensory and motor cortices as well as cognitive control networks.

For more than 2000 years Greek philosophers have thought about the puzzling introspectively assessed dichotomy between our physical bodies and our seemingly non-physical minds. How is it that we can think highly abstract thoughts, seemingly fully detached from actual, physical reality? Despite the obvious interactions between mind and body (we get tired, we are hungry, we stay up late despite being tired, etc.), until today it remains puzzling how our mind controls our body, and vice versa, how our body shapes our mind. Despite a big movement towards embodied cognitive science over the last 20 years or so, introductory books with a functional and computational perspective on how human thought and language capabilities may actually have come about – and are coming about over and over again – are missing. This book fills that gap. Starting with a historical background on traditional cognitive science and resulting fundamental challenges that have not been resolved, embodied cognitive science is introduced and its implications for how human minds have come and continue to come into being are detailed. In particular, the book shows that evolution has produced biological bodies that provide “morphologically intelligent” structures, which foster the development of suitable behavioral and cognitive capabilities. While these capabilities can be modified and optimized given positive and negative reward as feedback, to reach abstract cognitive capabilities, evolution has furthermore produced particular anticipatory control-oriented mechanisms, which cause the development of particular types of predictive encodings, modularizations, and abstractions. Coupled with an embodied motivational system, versatile, goal-directed, self-motivated behavior, learning becomes possible. These lines of thought are introduced and detailed from interdisciplinary, evolutionary, ontogenetic, reinforcement learning, and anticipatory predictive encoding perspectives in the first part of the book. A short excursus then provides an introduction to neuroscience, including general knowledge about brain anatomy, and basic neural and brain functionality, as well as the main research methodologies. With reference to this knowledge, the subsequent chapters then focus on how the human brain manages to develop abstract thought and language. Sensory systems, motor systems, and their predictive, control-oriented interactions are detailed from a functional and computational perspective. Bayesian information processing is introduced along these lines as are generative models. Moreover, it is shown how particular modularizations can develop. When control and attention come into play, these structures develop also dependent on the available motor capabilities. Vice versa, the development of more versatile motor capabilities depends on structural development. Event-oriented abstractions enable conceptualizations and behavioral compositions, paving the path towards abstract thought and language. Also evolutionary drives towards social interactions play a crucial role. Based on the developing sensorimotor- and socially-grounded structures, the human mind becomes language ready. The development of language in each human child then further facilitates the self-motivated generation of abstract, compositional, highly flexible thought about the present, past, and future, as well as about others. In conclusion, the book gives an overview over how the human mind comes into being – sketching out a developmental pathway towards the mastery of abstract and reflective thought, while detailing the critical body and neural functionalities, and computational mechanisms, which enable this development.

Artificial intelligence (AI) seeks to make computers do the sorts of things that minds can do, which involves psychological skills such as perception, association, prediction, planning, and motor control. Intelligence is a richly structured space of diverse information-processing capacities. Accordingly, AI uses many different techniques, addressing many different tasks. ‘What is Artificial Intelligence?’ explains the two main aims of AI: one being technological and the other scientific. It looks at AI’s influence on the life sciences and philosophy. Can any AI system possess real intelligence, creativity, or life? It also considers how AI began, virtual machines, the major types of AI, and cybernetics.

The cognitive predictors of mathematical abilities and disabilities/disorders (MD) were investigated. An overview is given of the prediction by early numeracy skills such as Piagetian logical thinking, counting, and number comparison skills. In addition, studies of relationships between language and numeracy in kindergarten and grade 1 are discussed. Moreover, the chapter sought out to extend our knowledge regarding the relationship between motor, visual and visuomotor skills and mathematical abilities and disabilities. Furthermore, the chapter discusses studies of working memory, inhibition, naming speed and inference control as cognitive predictors for mathematical abilities and MD. Finally findings about the sensitivity of number sense for MD are provided.

Neuroimaging studies have increased our understanding of the neurobiological underpinnings of ADHD. Structural brain imaging studies demonstrate widespread changes in brain volumes, in particular in frontal-striatal-cerebellar networks. Based on the widespread nature of structural and functional brain abnormalities, approaches able to capture the organizing principles of large-scale neural systems have been used in ADHD. These include diffusion magnetic resonance imaging (MRI) and resting state functional MRI (R-fMRI). Complementary to findings of volumetric studies, diffusion investigations have reported structural connectivity abnormalities in frontal-striatal-cerebellar networks. In parallel, R-fMRI studies point towards abnormalities in the interaction of multiple networks, extending the functional territory of explorations beyond cognitive and motor control. In the future, a deep phenotypic characterization beyond diagnostic categories combined with longitudinal study designs and novel analytical approaches will accelerate the pace towards clinical translations of neuroimaging to improve the detection and prediction of neural trajectories and treatment response in ADHD.