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Hybrid systems, optimal control and hybrid vehicles : theory, methods and applications /
This book assembles new methods showing the automotive engineer for the first time how hybrid vehicle configurations can be modeled as systems with discrete and continuous controls. These hybrid systems describe naturally and compactly the networks of embedded systems which use elements such as inte...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham, Switzerland :
Springer,
2017.
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| Colección: | Advances in industrial control.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Series Editors' Foreword; Preface; Intended Readership; What are the Contributions of This Book; What is Not Covered in This Book; Structure of the Book; Acknowledgements; Contents; Abbreviations and Symbols; 1 Introduction; 1.1 Motivation, Challenges, and Objectives; 1.2 Vehicle Design Aspects; 1.2.1 Stages of Energy Conversion; 1.2.2 Real-World Driving Profile, Consumption, and Emissions; 1.3 Process Model, Control Strategy, and Optimization; 1.3.1 General Problem Statement; 1.3.2 Energy Management; 1.3.3 Numerical Solutions; 1.4 Bibliographical Notes; References.
- Part I Theory and Formulations2 Introduction to Nonlinear Programming; 2.1 Introduction; 2.2 Unconstrained Nonlinear Optimization; 2.2.1 Necessary and Sufficient Conditions for Optimality; 2.2.2 Newton
- Raphson Method; 2.2.3 Globalization of the Newton
- Raphson Method; 2.2.4 Quasi-Newton Method; 2.3 Constrained Nonlinear Optimization; 2.3.1 Necessary and Sufficient Conditions for Optimality; 2.3.2 Projected Hessian; 2.3.3 Sequential Quadratic Programming; 2.4 Sensitivity Analysis; 2.4.1 Sensitivity Analysis of the Objective Function and Constraints; 2.4.2 Linear Perturbations.
- 2.4.3 Approximation of the Perturbed Solution2.4.4 Approximation of the Confidence Region; 2.5 Multi-Objective Optimization; 2.5.1 Elitist Multi-Objective Evolutionary Algorithm; 2.5.2 Remarks for MOGAs; 2.6 Bibliographical Notes; References; 3 Hybrid Systems and Hybrid Optimal Control; 3.1 Introduction; 3.2 System Definition; 3.2.1 Continuous Systems; 3.2.2 Hybrid Systems; 3.2.3 Controlled Hybrid Systems and Switched Systems; 3.2.4 Existence and Uniqueness of Admissible States and Controls; 3.2.5 Control and State Constraints, Admissible Sets, and Admissible Function Spaces.
- 3.2.6 Reformulation of Switched Systems3.3 Optimal Control Problem Formulations; 3.3.1 Functionals; 3.3.2 Boundary Conditions; 3.3.3 Continuous Optimal Control Problem; 3.3.4 Hybrid Optimal Control Problem; 3.3.5 Switched Optimal Control Problem; 3.3.6 Binary Switched Optimal Control Problem; 3.3.7 Transformations of Optimal Control Problems; 3.4 Bibliographical Notes; References; 4 The Minimum Principle and Hamilton
- Jacobi
- Bellman Equation; 4.1 Introduction; 4.1.1 The Calculus of Variations; 4.1.2 Deriving First-Order Necessary Conditions for an Extremum of an Optimal Control Problem.
- 4.2 Minimum Principle4.2.1 Necessary Conditions for Optimal Control Problems with Control Restraints; 4.2.2 Necessary Conditions for Optimal Control Problems with State Constraints; 4.2.3 Necessary Conditions for Optimal Control Problems with Affine Controls; 4.3 Hamilton
- Jacobi
- Bellman Equation; 4.4 Hybrid Minimum Principle; 4.4.1 Necessary Conditions for Switched Optimal Control Problems Without State Jumps; 4.4.2 Necessary Conditions for Switched Optimal Control Problems with State Jumps; 4.4.3 Revisited: Necessary Conditions for a State Constrained Optimal Control Problem; 4.5 Existence.