Control Systems Benchmarks: (Advances in Industrial Control)

Control Systems Benchmarks helps control engineers, researchers, and students to evaluate and compare control system performance across a range of critical applications by offering a collection of real-world benchmarks. The book brings together challenges from diverse fields like power grids, robotics, automotive systems, and industrial processes, giving readers practical tools to test their control methods in realistic settings. Organized into two blocks, the book first tackles process control, covering dynamic and large-scale problems such as load-frequency control in power grids and wastewater-treatment-plant automation. The second block explores robotics and vehicles, focusing on areas like fault-tolerant control of quadrotors and lateral stability in electric vehicles. Each benchmark presents complex engineering challenges, allowing readers to experiment with various control approaches. This book is set apart by the consistent structure of its chapters, which enables readers to adapt benchmarks for their own systems 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; experimental setup, performance metrics, and data collection methods; downloadable materials and instructions for running simulations or accessing physical platforms; and a discussion of existing solutions, case studies, and open challenges to inspire further research. Whether you're a practitioner, an academic researcher, or a student eager to deepen your understanding of control systems, Control Systems Benchmarks offers practical insights and valuable resources to advance your work.  

Table of Contents:
Chapter 1. A collection of benchmarks for control engineers.- Part 1. Processes.- Chapter 2. A benchmark for the application of distributed control techniques to the electricity network of the European economic area.- Chapter 3. Agroconnect research station: General description and control challenges.- Chapter 4. Temperature control of a shrink tunnel with multiple heating zones.- Chapter 5. A model for gas humidification in a fuel-cell assembly.- Chapter 6. A benchmark for plant-wide optimization and control of activated sludge wastewater treatment plants.- Chapter 7. On a benchmark problem for automated insulin delivery in type-1 diabetes.- Chapter 8. Advances in run-to-fail ball bearing testbench: Bridging the gap in predictive maintenance.- Part II. Robots and Vehicles.- Chapter 9. Fault-tolerant control of a quadrotor based on a nonlinear model.- Chapter 10. A benchmark on formation control of Multi-Agent Robotic System.- Chapter 11. Digital twin and scaled prototype: Open low-cost benchmarks for mobile robotics.- Chapter 12. Benchmarking handling performance in 4WD electric vehicles through advanced control techniques.- Chapter 13. Benchmark problem for visual nudge: Light-guided control of human driven vehicles.

About the Author :
Professor José M. Maestre holds a PhD from the University of Seville, where he currently works as a full professor. He has held various positions at universities such as TU Delft, University of Pavia, Kyoto University and Tokyo Institute of Technology. His research focuses on the control of distributed cyber-physical systems, with a special emphasis on the integration of heterogeneous agents in the control loop. He has published more than 200 journal and conference papers, co-edited several books, and led multiple research projects. Finally, his achievements have been recognized through several awards and honors, including the Spanish Royal Academy of Engineering's medal for his contributions to the predictive control of large-scale systems. Professor Carlos Ocampo-Martinez, Doctor in Control Engineering from the Universitat Politècnica de Catalunya – BarcelonaTECH, has been actively involved in research and development activities pertaining to the management and control of water and energy systems. His research focuses on evolutionary game theory, model predictive control strategies, distributed optimization approaches for large-scale network management, and the management and control of large-scales systems. Professor Ocampo-Martinez has written more than a hundred of high-qualityjournal articles on a variety of issues, including decentralised control for urban water and energy systems, model predictive control of complex networks, and management/control of clean energy production devices.