**Section 4 Robust Adaptive Controls of Overhead Cranes 291**

Chapter 15 **Robust Control of Crane with Perturbations 293** Yiming Wu, He Chen and Tong Yang

Chapter 7 **Matlab-Simulink-Based Compound Model Reference Adaptive**

Chapter 8 **Model Reference Adaptive Control of Quadrotor UAVs: A**

Chapter 9 **Adaptive Nonlinear Regulation Control of Thermoacoustic Oscillations in Rijke-Type Systems 161**

William MacKunis, Mahmut Reyhanoglu and Krishna Bhavithavya

Shunya Nagai, Hidetoshi Oya, Tsuyoshi Matsuki and Yoshikatsu

Jian Chen, Peng Li, Gangbing Song, Shubo Wang, Zichao Zhang,

**Fast Tracking and Faulty-Tolerant Control Performance in**

Yi Zhang, Kairui Guo, Qin Yang, Pang Winnie, Kai Cao, Qi Wang, Andrey Savkin, Branko Celler, Hung Nguyen, Peng Xu, Limei Xu,

**Control for DC Motor 117**

**Neural Network Perspective 135**

**Section 3 Other Robust Adaptive Control Systems 183**

**Dynamical Systems 185**

Chapter 11 **Robust Control Applications to a Wind Turbine-Simulated System 217** Silvio Simani and Paolo Castaldi

Chapter 12 **Adaptive Robust Control of Biomass Fuel Co-Combustion Process 235**

**Treadmill Exercises 275**

Dezhong Yao and Steven Su

Konrad Gromaszek and Andrzej Kotyra

Chapter 13 **A CMAC-Based Systematic Design Approach of an Adaptive Embedded Control Force Loading System 255**

Chapter 14 **Multi-Loop Integral Control-Based Heart Rate Regulation for**

Guangqi Wang, Yu Tan and Yongjun Zheng

Chapter 10 **Adaptive Gain Robust Control Strategies for Uncertain**

Marian Găiceanu

**VI** Contents

Nikhil Angad Bakshi

Kidambi

Hoshi


Preface

advantages:

disturbances.

ters are classified into four groups as follows:

We would like to introduce to the readers a monograph related to *robust adaptive control and its application*. The book presents the recent studies on applications of robust and adaptive control approaches to practical systems. Being a generalized concept, robust adaptive con‐ trol indicates the control techniques that make the systems stable, work well, and robust de‐ spite the actions of uncertainties and disturbances. In addition, the controlled systems tend to the adaptive features, in which the systems show the ability in self-changing and self-ad‐ justing the control structures to adapt to the influences of uncertainties. Robust control re‐ quires the information of all plant parameters, and these parameters must lie in the deterministic boundaries. Meanwhile, adaptive control does not need to know many system parameters even the system structure because the adaption mechanisms are integrated for dealing with parametric uncertainties, parameter estimation, and structural approximation. Robust control simply keeps the consistence of system responses, while adaptive control makes the systems to self-learn or self-train to achieve the control objectives. In this regard, adaptive control is more superior to robust control. Otherwise, robust control holds the strong points that adaptive control does not have. Robust control can treat well the prob‐ lems of quick varying parameters, while adaptive control is only effective in case of slow parametric uncertainties. In addition, robust control is better for control problems with dis‐ turbances and modeling imprecision. The combination of robust control methods and adap‐ tive control techniques leads to the *robust adaptive control systems* having two key

(I) *Robustness*: The control system is robust with the large variation in plant parameters and

(II) *Adaptation*: The control system does not need the knowledge of plant parameters even the plant model. The adaptation behavior will automatically find the proper estimated pa‐ rameters even synthetizing the approximated model to support the controller working well. Tending to robust adaptive control systems, the studies in this book consisting of 17 chap‐

(1) *Advanced sliding mode control* (SMC): As a key approach of robust controls, SMC has been largely applied in designing the control systems with robust features. SMC does not require much accuracy of plant model. It treats well the systems having widely varying parameters and disturbances. However, chattering phenomenon of system responses is a challenge that needs to be solved completely in conventional SMC. Chapter 1 integrates the fuzzy approach into two robust control methods composed of SMC and H-infinity to construct two adaptive robust controllers for reducing the vibration of vehicle seat suspension systems under the excitation of several road profiles. Chapter 2 designs the guidance system for aircrafts based
