Design of Delay-Based Controllers for Linear Time-Invariant Systems


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By Adrian Ramirez, Rifat Sipahi, Sabine Mondie, Ruben Garrido
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SIAM - SOCIETY FOR INDUSTRIAL AND APPLIED
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PAPERBACK
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184

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Description

Adrian Ramirez is a professor in the Division of Control and Dynamical Systems at IPICYT, working under the CONAHCYT program: Investigadoras e Investigadores por Mexico. His research focuses on exploring the beneficial and detrimental effects of time delays in dynamical systems with applications in robotics, multi-agent systems, and power electronics. Rifat Sipahi is a professor in the Department of Mechanical and Industrial Engineering at Northeastern University in Boston. He is the recipient of a 2011 DARPA Young Faculty Award and the 2015 ASME Dynamic Systems and Control Division Outstanding Young Investigator Award, a Fellow of ASME and a senior member of IEEE, and an associate editor for Automatica. His research interests include stability, stabilization of dynamical systems at the interplay between multiple time delays and network graphs, human-machine systems, and human-robotic interactions. Sabine Mondie is a professor and head of the Department of Automatic Control at CINVESTAV-IPN in Mexico. She has been chair of education, vice-chair of the IFAC Technical Committee 2.2 on Linear Control Systems, and a member of the IFAC Council for the 2023-2026 triennium. She has served as associate editor for several journals, including IEEE Transactions on Automatic Control, Systems & Control Letters, and European Journal of Control. Her research focuses on time-delay systems and their stability and robustness properties, as well as delay applications in engineering and biology. Ruben Garrido is a professor in the Department of Automatic Control at CINVESTAV-IPN in Mexico, where he is responsible for experimental services. His research interests include serial and parallel robot control, visual servoing, servomechanism control, adaptive control, delay-based control, neural networks-based control, parameter identification, and tuning of feedback controllers using bio-inspired metaheuristics.

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