内容简介：　　

　 Advanced Control of Wheeled Inverted Pendulum Systems is an orderly presentation of recent ideas for overcoming the complications inherent in the control of wheeled inverted pendulum (WIP) systems, in the presence of uncertain dynamics, nonholonomic kinematic constraints as well as underactuated configurations. The text leads the reader in a theoretical exploration of problems in kinematics, dynamics modeling, advanced control design techniques and trajectory generation for WIPs. An important concern is how to deal with various uncertainties associated with the nominal model, WIPs being characterized by unstable balance and unmodelled dynamics and being subject to time-varying external disturbances for which accurate models are hard to come by.

　 The book is self-contained, supplying the reader with everything from mathematical preliminaries and the basic Lagrange-Euler-based derivation of dynamics equations to various advanced motion control and force control approaches as well as trajectory generation method. Although primarily intended for researchers in robotic control, Advanced Control of Wheeled Inverted Pendulum Systems will also be useful reading for graduate students studying nonlinear systems more generally.


英文目录：
1 Introduction
　　1.1 An Overview of WIP Robots
　　1.2 Difficulties of Controlling WIP Systems
　　1.3 Outline of Book
2 Mathematical Preliminaries
　　2.1 Introduction
　　2.2 Matrix Algebra
　　2.3 Norms for Functions
　　2.4 Definitions
　　2.5 Lemmas and Theorems
　　2.6 Input-to-State Stability
　　2.7 Lyapunov's Direct Method
　　2.8 Barbalat-Like Lemmas
　　2.9 Controllability and Observability of Nonlinear Systems
　　　　2.9.1 Controllability
　　　　2.9.2 Observability
　　　　2.9.3 Brockett’s Theorem on Feedback Stabilization
　　2.10 Lyapunov Theorems
　　2.11 Notes and References
3 Modeling of WIP Systems
　　3.1 Introduction
　　3.2 Kinematics of the WIP Systems
　　3.3 Dynamics of WIP Systems
　　　　3.3.1 Lagrange–Euler Equations
　　　　3.3.2 Kinetic Energy
　　　　3.3.3 Potential Energy
　　　　3.3.4 Lagrangian Equations
　　　　3.3.5 Properties of Mechanical Dynamics
　　　　3.3.6 Dynamics of Wheeled Inverted Pendulum
　　3.4 Newton–Euler Approach
　　3.5 Conclusion
4 Linear Control
　　4.1 Introduction
　　4.2 Linearization of the WIP Dynamics
　　4.3 PD Control Design
　　4.4 LQR based Optimal Control Design
　　4.5 H∞ Control
　　　　4.5.1 Riccati-Based H∞ Control
　　　　4.5.2 LMI-Based H∞ Control
　　4.6 Backstepping
　　4.7 Simulation Studies
　　　　4.7.1 PD Control
　　　　4.7.2 LQR Control
　　　　4.7.3 H∞-Like Riccati Control
　　　　4.7.4 LMI-Based H∞ Control
　　　　4.7.5 Backstepping Control
　　4.8 Conclusion
5 Nonlinear Control
　　5.1 Introduction
　　5.2 Preliminaries
　　5.3 System Dynamics
　　5.4 Nonlinear Feedback Linearization
　　5.5 Model Based Control Design
　　5.6 Model-Based Disturbance Rejection Control
　　5.7 Simulation Studies
　　5.8 Conclusion
6 Adaptive Control
　　6.1 Introduction
　　6.2 Motion Control
　　　　6.2.1 Adaptive Robust Control Design
　　　　6.2.2 Zero-Dynamics Stability Analysis
　　　　6.2.3 Simulation Studies
　　6.3 Hybrid Force and Motion Control
　　　　6.3.1 Preliminaries and Dynamics Transformation
　　　　6.3.2 Motion Control of z2 and z3-Subsystems
　　　　6.3.3 Stability Analysis of the z1-Subsystem
　　　　6.3.4 Force Control
　　　　6.3.5 Simulation Studies
　　　　6.3.6 Conclusions
7 Intelligent Control
　　7.1 Introduction
　　7.2 SVM Control
　　　　7.2.1 Preliminaries
　　　　7.2.2 Reduced Dynamics and Physical Properties
　　　　7.2.3 LS-SVM Based Model Learning
　　　　7.2.4 LS-SVM Based Control Design
　　　　7.2.5 Simulation Studies
　　7.3 Fuzzy Control
　　　　7.3.1 Preliminaries
　　　　7.3.2 Functional Universal Approximation Using FLSs
　　　　7.3.3 Adaptive Fuzzy Control
　　　　7.3.4 Simulation Studies
　　7.4 Neural Network Output Feedback Control
　　　　7.4.1 Preliminaries
　　　　7.4.2 Neural Networks and Parametrization
　　7.5 Problem Formulation
　　　　7.5.1 Output Feedback Control
　　　　7.5.2 Stability Analysis
　　　　7.5.3 Simulation Studies
　　　　7.5.4 Conclusions
8 Optimized Model Reference Adaptive Control
　　8.1 Introduction
　　8.2 Preliminaries
　　　　8.2.1 Finite Time Linear Quadratic Regulator
　　　　8.2.2 HONN Approximation
　　8.3 Dynamics of Wheeled Inverted Pendulums
　　8.4 Control of ζ1 and ζ3-Subsystems
　　　　8.4.1 Subsystem Dynamics
　　　　8.4.2 Optimal Reference Model
　　　　8.4.3 Model Matching Error
　　　　8.4.4 Adaptive Control Design
　　　　8.4.5 Controller Structure
　　　　8.4.6 Control Performance Analysis
　　8.5 Reference Trajectory Generator for ζ2 Subsystem
　　8.6 Simulation Studies
　　8.7 Conclusion
9 Neural Network Based Model Reference Control
　　9.1 Introduction
　　9.2 Preliminaries
　　　　9.2.1 Radial Basis Function Neural Network
　　　　9.2.2 Block Matrix Operation
　　9.3 Dynamics of Wheeled Inverted Pendulums
　　9.4 Control of Angular Motion Subsystems
　　　　9.4.1 Optimized Reference Model
　　　　9.4.2 Adaptive NN Model Reference Control
　　9.5 Adaptive Generator of Implicit Control Trajectory
　　9.6 Simulation Studies
　　9.7 Conclusion
References
Index