Principled Controller Design: Theory, Analysis, and Practical Strategies for Robust Feedback Systems (eBook, ePUB)
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Principled Controller Design: Theory, Analysis, and Practical Strategies for Robust Feedback Systems is an authoritative and comprehensive resource that equips engineers, researchers, and students with a rigorous foundation in both the theory and practice of modern control. Beginning with precise system modeling and a unified treatment of stability and performance criteria, the text develops core methodologies-PID tuning, frequency-domain analysis, and state-space synthesis-while seamlessly connecting classical designs to contemporary innovations. Each chapter emphasizes principled reasoning, ...
Principled Controller Design: Theory, Analysis, and Practical Strategies for Robust Feedback Systems is an authoritative and comprehensive resource that equips engineers, researchers, and students with a rigorous foundation in both the theory and practice of modern control. Beginning with precise system modeling and a unified treatment of stability and performance criteria, the text develops core methodologies-PID tuning, frequency-domain analysis, and state-space synthesis-while seamlessly connecting classical designs to contemporary innovations. Each chapter emphasizes principled reasoning, guiding readers from mathematical fundamentals to actionable controller architectures.
The book offers in-depth coverage of advanced topics essential for modern applications: digital and discrete-time controllers, nonlinear and adaptive strategies, and robust techniques for managing model uncertainty. Readers will find clear expositions of Lyapunov-based methods, optimal control, H-infinity synthesis, and the design of networked and distributed systems. Special attention is given to data-driven and learning-augmented approaches, showing how AI and machine learning integrate with control theory to produce cooperative, adaptive, and resilient solutions for complex, interconnected systems.
Practical deployment is woven throughout the narrative, with hands-on guidance for simulation, rapid prototyping, embedded implementation, certification, and formal verification in safety-critical domains. Hardware considerations, real-world constraints, and industry case studies-from aerospace to advanced manufacturing-ensure the material remains grounded in engineering practice. By bridging theoretical rigor with pragmatic strategies, this book serves as an indispensable reference for those designing robust feedback systems in today's dynamic technological landscape.
The book offers in-depth coverage of advanced topics essential for modern applications: digital and discrete-time controllers, nonlinear and adaptive strategies, and robust techniques for managing model uncertainty. Readers will find clear expositions of Lyapunov-based methods, optimal control, H-infinity synthesis, and the design of networked and distributed systems. Special attention is given to data-driven and learning-augmented approaches, showing how AI and machine learning integrate with control theory to produce cooperative, adaptive, and resilient solutions for complex, interconnected systems.
Practical deployment is woven throughout the narrative, with hands-on guidance for simulation, rapid prototyping, embedded implementation, certification, and formal verification in safety-critical domains. Hardware considerations, real-world constraints, and industry case studies-from aerospace to advanced manufacturing-ensure the material remains grounded in engineering practice. By bridging theoretical rigor with pragmatic strategies, this book serves as an indispensable reference for those designing robust feedback systems in today's dynamic technological landscape.
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