Model Predictive Control for Complex Dynamic Systems by Yan Song(.PDF)
File Size: 15.1 MB
Model Predictive Control for Complex Dynamic Systems: Analysis and Synthesis by Yan Song, Zidong Wang, Bin Zhang
Requirements: .PDF reader, 15.1 MB | True PDF
Overview: Model Predictive Control (MPC) has advanced as a robust method for managing complex dynamic systems, surpassing traditional control strategies in performance and constraint handling. This book explores MPC theory and applications, focusing on robust MPC (RMPC) for systems with uncertainties. It examines three system types: networked systems, stochastic switching systems, and nonlinear hybrid systems. It addresses challenges in networked interventions, Markovian jump systems, and nonlinear systems under communication constraints. The field of control science and system engineering has witnessed significant advancements in recent years, particularly in the area of Model Predictive Control (MPC). MPC has emerged as a powerful technique for controlling complex and dynamic systems, exhibiting advantages over traditional control strategies in terms of performance and robustness. This book, “Model Predictive Control for Complex Dynamic Systems—Analysis and Synthesis”, aims to provide a comprehensive overview of MPC theory and its applications in a variety of challenging dynamic systems.
Genre: Non-Fiction > Tech & Devices
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