Control Systems Benchmarks II helps control engineers, researchers, and students to evaluate and compare closed-loop control system performance across a range of critical applications by offering a collection of real-world case studies. The book expands on the range of benchmarks provided in the earlier sister volume (978-3-031-76311-3).

The range of subjects covered spans applications from clean power production to manufacturing and autonomous systems, including concentrated solar power generation, fast charging of batteries, and nuclear fusion plasma control. Each benchmark represents a complex engineering challenge, allowing readers to design and compare different control and estimation approaches across diverse scenarios.

This book follows the consistent chapter structure established in the previous volume, enabling readers to adapt benchmarks to their own interests easily. Each chapter includes:

• a brief overview of the benchmark, highlighting its significance and technical hurdles;
• a detailed problem description, including engineering goals and constraints;
• benchmark design, including experimental setup, performance metrics, and data collection methods; and
• access information for downloadable materials and instructions for running simulations or accessing physical platforms.

Whether you're a practitioner looking for usable control solutions, an academic researcher seeking meaningful examples, or a student looking for practical knowledge of control systems, Control Systems Benchmarks II offers valuable insights and resources to advance your work.

Professor José M. Maestre holds a PhD from the University of Seville, where he currently serves as a full professor. He has held positions at universities such as TU Delft, University of Pavia, Kyoto University and the Institute of Science Tokyo (formerly Tokyo Institute of Technology). He is author of Service Robotics within the Digital Home (Springer, 2011), A Programar se Aprende Jugando (Paraninfo, 2017), and Sistemas de Medida y Regulación (Paraninfo, 2018), co-author of Model Predictive Control, 3rd edition (Springer, 2026), and also editor of Distributed Model Predictive Control Made Easy (Springer, 2014) and Control Systems Benchmarks (Springer, 2025). His research focuses on the control of distributed cyber-physical systems, with a special emphasis on integrating heterogeneous agents into the control loop. He has published more than 200 journal and conference papers and has led multiple research projects. Finally, his achievements have been recognized with several awards and honors, including the Spanish Royal Academy of Engineering’s medal for his contributions to predictive control in large-scale systems.

Professor Carlos Ocampo-Martinez is a Full Professor of Automatic Control at the Universitat Politècnica de Catalunya – BarcelonaTech (UPC), where he has been a faculty member of the Automatic Control Department since 2011. He received his Ph.D. in Automatic Control from UPC, with research focused on model predictive control, hybrid systems, and fault-tolerant control. His scientific activity addresses the analysis, optimization, and control of complex large-scale systems, with particular emphasis on constrained and distributed model predictive control, evolutionary game theory, distributed optimization, and process control. His work has been applied to urban water networks, wastewater systems, energy systems, hydrogen and fuel-cell technologies, smart manufacturing, and industrial cyber-physical systems. Professor Ocampo-Martinez has authored more than a hundred journal papers and several book contributions, establishing a strong international profile in predictive control, non-centralized decision-making, and sustainable infrastructure management.