Control Systems Benchmarks
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Control Systems Benchmarks
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.
Process Control Performance Assessment
Author: Andrzej Ordys
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-05-19
This book is a practical guide to the application of control benchmarking to real, complex, industrial processes. The variety of industrial case studies gives the benchmarking ideas presented a robust real-world attitude. The book deals with control engineering principles and economic and management aspects of benchmarking. It shows the reader how to avoid common problems in benchmarking and details the benefits of effective benchmarking.
Process Control System Fault Diagnosis
Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc., Canada Biao Huang, University of Alberta, Canada Data-driven Inferential Solutions for Control System Fault Diagnosis A typical modern process system consists of hundreds or even thousands of control loops, which are overwhelming for plant personnel to monitor. The main objectives of this book are to establish a new framework for control system fault diagnosis, to synthesize observations of different monitors with a prior knowledge, and to pinpoint possible abnormal sources on the basis of Bayesian theory. Process Control System Fault Diagnosis: A Bayesian Approach consolidates results developed by the authors, along with the fundamentals, and presents them in a systematic way. The book provides a comprehensive coverage of various Bayesian methods for control system fault diagnosis, along with a detailed tutorial. The book is useful for graduate students and researchers as a monograph and as a reference for state-of-the-art techniques in control system performance monitoring and fault diagnosis. Since several self-contained practical examples are included in the book, it also provides a place for practicing engineers to look for solutions to their daily monitoring and diagnosis problems. Key features: • A comprehensive coverage of Bayesian Inference for control system fault diagnosis. • Theory and applications are self-contained. • Provides detailed algorithms and sample Matlab codes. • Theory is illustrated through benchmark simulation examples, pilot-scale experiments and industrial application. Process Control System Fault Diagnosis: A Bayesian Approach is a comprehensive guide for graduate students, practicing engineers, and researchers who are interests in applying theory to practice.