Yan Song – författare

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.

• Integrates model predictive control, network-induced constraints, cyber-security issues, and advanced communication protocols• Covers control and state estimation with a focus on dynamic network systems with complex sampling• Considers and models network-induced complexities• Employs several analysis techniques to overcome the recent mathematical/computational difficulties for discrete-time systems• Deals with practical engineering problems for complex dynamic systems with different kinds of scenario-induced complexities or frame-work-induced complexities

This book is aimed at graduate students and researchers in networks, signal processing, controls, and dynamic complex systems.

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.

• Integrates model predictive control, network-induced constraints, cyber-security issues, and advanced communication protocols• Covers control and state estimation with a focus on dynamic network systems with complex sampling• Considers and models network-induced complexities• Employs several analysis techniques to overcome the recent mathematical/computational difficulties for discrete-time systems• Deals with practical engineering problems for complex dynamic systems with different kinds of scenario-induced complexities or frame-work-induced complexities

This book is aimed at graduate students and researchers in networks, signal processing, controls, and dynamic complex systems.

The coalbed methane (CBM) reserve in China ranks third in the world with a total resource of 36.8×1012 m3. Exploitation of CBM has an important practical significance to ensure the long-term rapid development of China natural gas industry. Therefore, in 2002, the Ministry of Science and Technology of China set up a national 973 program to study CBM system and resolve problems of CBM exploration and exploitation in China. All the main research results and new insights from the program are presented in this book.  

The book is divided into 11 chapters. The first chapter mainly introduces the present situation of CBM exploration and development in China and abroad. Chapters 2 through 9 illustrate the geological theory and prospect evaluation methods. Then chapters 10 and 11 discuss CBM recovery mechanisms and technology. The book systematically describes the origin, storage, accumulation and emission of CBM in China, and also proposes new methods and technologies on resource evaluation, prospect prediction, seismic interpretation and enhanced recovery. The book will appeal to geologists, lecturers and students who are involved in the CBM industry and connected with coal and conventional hydrocarbon resources research.