Modern engineered systems do not fit neatly inside one subject—and neither should the way you learn to analyze them.
A real feedback system links physical dynamics, measurements, estimation, communication, computation, decision-making, actuation, uncertainty, constraints, and human oversight. Learning these topics separately can leave a critical gap: understanding how the complete loop behaves when noise, delay, model error, saturation, changing conditions, or faults appear.
Fundamentals of Engineering Cybernetics closes that gap with a structured engineering path from mathematical foundations and system modeling to advanced control, estimation, optimization, learning, robotics, and resilient cyber-physical systems. The emphasis is not only on obtaining a numerical answer, but on understanding the assumptions, units, validity limits, and evidence behind it.
Inside, you will explore how to:The manuscript is specifically structured around these interconnected areas, progressing from mathematical foundations through control and estimation to optimization, intelligent control, robotics, distributed cyber-physical systems, safety, and resilience.
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Paperback. Etat : new. Paperback. Modern engineered systems do not fit neatly inside one subject-and neither should the way you learn to analyze them.A real feedback system links physical dynamics, measurements, estimation, communication, computation, decision-making, actuation, uncertainty, constraints, and human oversight. Learning these topics separately can leave a critical gap: understanding how the complete loop behaves when noise, delay, model error, saturation, changing conditions, or faults appear.Fundamentals of Engineering Cybernetics closes that gap with a structured engineering path from mathematical foundations and system modeling to advanced control, estimation, optimization, learning, robotics, and resilient cyber-physical systems. The emphasis is not only on obtaining a numerical answer, but on understanding the assumptions, units, validity limits, and evidence behind it.Inside, you will explore how to: Build dynamic and state-space models from clearly defined variables, boundaries, assumptions, and physical relationships.Connect feedback and stability with classical design, state feedback, optimal control, observers, Kalman filtering, and sensor fusion.Account for sampling, quantization, communication delay, jitter, packet loss, actuator limits, and numerical implementation.Explore constrained optimization, model predictive control, robust and adaptive methods, and learning-augmented control with validation and fallback in view.Extend the same framework to robotics, autonomy, multi-agent coordination, digital twins, cybersecurity, safety, resilience, and human-machine assurance.Reinforce learning through transparent derivations, SI-unit calculations, worked examples, practice problems, cross-references, and practical appendix checklists.The manuscript is specifically structured around these interconnected areas, progressing from mathematical foundations through control and estimation to optimization, intelligent control, robotics, distributed cyber-physical systems, safety, and resilience. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798191983448
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Taschenbuch. Etat : Neu. Neuware - Modern engineered systems do not fit neatly inside one subject-and neither should the way you learn to analyze them.A real feedback system links physical dynamics, measurements, estimation, communication, computation, decision-making, actuation, uncertainty, constraints, and human oversight. Learning these topics separately can leave a critical gap: understanding how the complete loop behaves when noise, delay, model error, saturation, changing conditions, or faults appear.Fundamentals of Engineering Cybernetics closes that gap with a structured engineering path from mathematical foundations and system modeling to advanced control, estimation, optimization, learning, robotics, and resilient cyber-physical systems. The emphasis is not only on obtaining a numerical answer, but on understanding the assumptions, units, validity limits, and evidence behind it.Inside, you will explore how to: - Build dynamic and state-space models from clearly defined variables, boundaries, assumptions, and physical relationships.- Connect feedback and stability with classical design, state feedback, optimal control, observers, Kalman filtering, and sensor fusion.- Account for sampling, quantization, communication delay, jitter, packet loss, actuator limits, and numerical implementation.- Explore constrained optimization, model predictive control, robust and adaptive methods, and learning-augmented control with validation and fallback in view.- Extend the same framework to robotics, autonomy, multi-agent coordination, digital twins, cybersecurity, safety, resilience, and human-machine assurance.- Reinforce learning through transparent derivations, SI-unit calculations, worked examples, practice problems, cross-references, and practical appendix checklists.The manuscript is specifically structured around these interconnected areas, progressing from mathematical foundations through control and estimation to optimization, intelligent control, robotics, distributed cyber-physical systems, safety, and resilience. N° de réf. du vendeur 9798191983448
Quantité disponible : 2 disponible(s)