Название: Cyber-physical Vehicle Systems: Methodology and Applications Автор: Chen LV, Yang Xing
Издательство: Morgan & Claypool
Год: 2020
Язык: английский
Формат: pdf (true)
Размер: 18.14 MB
This book studies the design optimization, state estimation, and advanced control methods for cyber-physical vehicle systems (CPVS) and their applications in real-world automotive systems.
Intelligent vehicles have been gaining increasing attention from both academia and industrial sectors. The field of intelligent vehicles exhibits a multidisciplinary nature, involving transportation, automotive engineering, information, energy, and security. Intelligent vehicles have increased their capabilities in highly and even fully automated driving. However, unresolved problems do exist due to strong uncertainties and complex human-vehicle interactions. Highly automated vehicles are likely to be on public roads within a few years. Before transitioning to fully autonomous driving, driver behavior should be better understood and integrated to enhance vehicle performance and traffic efficiency.
First, in Chapter 1, key challenges and state-of-the-art of vehicle design and control in the context of cyber-physical systems are introduced. In Chapter 2, a cyber-physical system (CPS) based framework is proposed for high-level co-design optimization of the plant and controller parameters for CPVS, in view of vehicle's dynamic performance, drivability, and energy along with different driving styles. System description, requirements, constraints, optimization objectives, and methodology are investigated. In Chapter 3, an Artificial-Neural-Network-based estimation method is studied for accurate state estimation of CPVS. In Chapter 4, a high-precision controller is designed for a safety-critical CPVS. The detailed control synthesis and experimental validation are presented. The application results presented throughout the book validate the feasibility and effectiveness of the proposed theoretical methods of design, estimation, control, and optimization for cyber physical vehicle systems.
Table of Contents:
1. Introductions
2. Co-Design Optimization for Cyber-Physical Vehicle System
2.2. System Modeling and Validation
2.3. Controller Design for Different Driving Styles
3. State Estimation of Cyber-Physical Vehicle Systems
3.1. Multilayer Artificial Neural Networks Architecture
3.2. Standard Backpropagation Algorithm
3.5.1. Results of the ANN-Based Braking Pressure Estimation
4. Controller Design of Cyber-Physical Vehicle Systems
4.3 Control Algorithm Design for Closed-Loop
5. Conclusions
References
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