Preface

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 advantages:

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

(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‐ ters are classified into four groups as follows:

(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

on SMC and simulates the two complex operation cases. Chapter 3 proposes an SMC control‐ ler for multimotor drive systems, integrates the high-gain observer, and considers the influ‐ ence of nonlinearities such as backlash, friction, and elasticity. Chapter 4 utilizes the stator flux–oriented SMC to regulate torque and reactive power of doubly fed induction generator.

lers on the basis of Lyapunov candidate and its barrier version. Finally, Chapter 17 uses the input-to-state stable method together with Lyapunov stability for constructing the robust control algorithms. The robustness of crane system when facing with parametric uncertain‐

This book is formed by the recent studies of many authors around the world. As an editor, I would like to thank all the authors for their excellent contributions to the book. I am also sincerely grateful to Mr. Slobodan at IntechOpen who helped me to manage the editorial process positively and effectively. Hopefully, the readers will find many useful information

Associate Professor at Automotive Engineering Department

Vietnam Maritime University, Haiphong, Vietnam Research Professor at Center of Wind Energy System Kunsan National University, Gunsan, South Korea

**Le Anh Tuan**

Preface XI

ties and disturbances is also analyzed and investigated.

and professional knowledge in this book.

(2) *Model reference adaptive control* (MRAC): Dissimilar to SMC whereas the control structure is fixed, MRAC systems tend to adaptation behavior in terms of parametric uncertainties by self-varying the control structures. In fact, the control structures are parameterized with re‐ spect to varying plant parameters, and the adaptation mechanisms are constituted to ap‐ proximate these uncertainties. Chapter 5 develops a MRAC-based robust tracking system and an autopilot for quadrotors considering the parametric uncertainties composed of trans‐ lational mass and inertial mass with the presence of wind disturbances. Chapter 6 applies MRAC to construct an attitude control system for unmanned quadcopters when faced with unknown plant parameters, the action of disturbances, and the influence of nonlinearities in actuators. Chapter 7 designs the control algorithms for DC motors on the basis of compound MRAC, whereas the system robustness is investigated by using simulation. Chapter 8 en‐ hances MRAC for quadrotor unmanned aerial vehicles with the foundation of neural net‐ works and machine learning. On the basis of improved MRAC, Chapter 9 analyzes and designs an adaptive controller including SMC observers and parametric estimators for ther‐ mo-acoustic oscillations of Rijke-type systems with the presence of dynamic model uncer‐ tainty and unknown disturbances.

(3) *The other robust adaptive control approaches*: In this part, the other adaptive techniques such as gain-scheduling and fuzzy logic together with robust controls such as H-infinity are unti‐ tled for analyzing and designing the control systems. Chapter 10 synthesizes the robust adaptive controllers for a class of mechanical linear systems with adjustable time-varying parameters taking uncertainties and perturbation into account. Chapter 11 provides two kinds of adaptive robust control strategies for wind turbines using fuzzy logic, data-driven, and model-based approaches fully considering the stochastic disturbances and load uncer‐ tainties. Using model predictive control together with MRAC, Chapter 12 develops the proc‐ ess control system for biomass fuel cocombustion. Chapter 13 improves an adaptive embedded control system for measuring yield strength of plate-formed materials, in which a cerebellar model articulation controller (CMAC) is integrated in feedforward loop, and a proportional-derivative structure is equipped on feedback loop for training CMAC. With high applicability in medical practice and sport science, Chapter 14 proposes an adaptive control system for regulating the heart rate during treadmill exercises.

(4) *Control of overhead cranes—the underactuated systems*: We usually face with underactuated systems in control engineering practice. Overhead crane is an underactuated system, where‐ as the number of actuators is lesser than that of outputs. For 2D motion, only two actuators composed of trolley-moving motors and cargo-hosting motors are utilized for controlling three outputs. For 3D motion, three motors are applied for driving five outputs composed of trolley motion, bridge motion, cargo hoisting displacement, and two cargo swing angles. Control of such a system is harder than full-actuator systems and meets many challenges. This part introduces the robust and adaptive control techniques applied for overhead cranes and the symbolic underactuated mechanical systems. Chapter 15 proposes a robust nonlin‐ ear controller integrating state observer by using Lyapunov-based design, in which controll‐ ability and observability are also investigated. Chapter 16 constitutes a distributed mass model of overhead crane with flexible handling cable and proposes two nonlinear control‐ lers on the basis of Lyapunov candidate and its barrier version. Finally, Chapter 17 uses the input-to-state stable method together with Lyapunov stability for constructing the robust control algorithms. The robustness of crane system when facing with parametric uncertain‐ ties and disturbances is also analyzed and investigated.

on SMC and simulates the two complex operation cases. Chapter 3 proposes an SMC control‐ ler for multimotor drive systems, integrates the high-gain observer, and considers the influ‐ ence of nonlinearities such as backlash, friction, and elasticity. Chapter 4 utilizes the stator flux–oriented SMC to regulate torque and reactive power of doubly fed induction generator. (2) *Model reference adaptive control* (MRAC): Dissimilar to SMC whereas the control structure is fixed, MRAC systems tend to adaptation behavior in terms of parametric uncertainties by self-varying the control structures. In fact, the control structures are parameterized with re‐ spect to varying plant parameters, and the adaptation mechanisms are constituted to ap‐ proximate these uncertainties. Chapter 5 develops a MRAC-based robust tracking system and an autopilot for quadrotors considering the parametric uncertainties composed of trans‐ lational mass and inertial mass with the presence of wind disturbances. Chapter 6 applies MRAC to construct an attitude control system for unmanned quadcopters when faced with unknown plant parameters, the action of disturbances, and the influence of nonlinearities in actuators. Chapter 7 designs the control algorithms for DC motors on the basis of compound MRAC, whereas the system robustness is investigated by using simulation. Chapter 8 en‐ hances MRAC for quadrotor unmanned aerial vehicles with the foundation of neural net‐ works and machine learning. On the basis of improved MRAC, Chapter 9 analyzes and designs an adaptive controller including SMC observers and parametric estimators for ther‐ mo-acoustic oscillations of Rijke-type systems with the presence of dynamic model uncer‐

(3) *The other robust adaptive control approaches*: In this part, the other adaptive techniques such as gain-scheduling and fuzzy logic together with robust controls such as H-infinity are unti‐ tled for analyzing and designing the control systems. Chapter 10 synthesizes the robust adaptive controllers for a class of mechanical linear systems with adjustable time-varying parameters taking uncertainties and perturbation into account. Chapter 11 provides two kinds of adaptive robust control strategies for wind turbines using fuzzy logic, data-driven, and model-based approaches fully considering the stochastic disturbances and load uncer‐ tainties. Using model predictive control together with MRAC, Chapter 12 develops the proc‐ ess control system for biomass fuel cocombustion. Chapter 13 improves an adaptive embedded control system for measuring yield strength of plate-formed materials, in which a cerebellar model articulation controller (CMAC) is integrated in feedforward loop, and a proportional-derivative structure is equipped on feedback loop for training CMAC. With high applicability in medical practice and sport science, Chapter 14 proposes an adaptive

(4) *Control of overhead cranes—the underactuated systems*: We usually face with underactuated systems in control engineering practice. Overhead crane is an underactuated system, where‐ as the number of actuators is lesser than that of outputs. For 2D motion, only two actuators composed of trolley-moving motors and cargo-hosting motors are utilized for controlling three outputs. For 3D motion, three motors are applied for driving five outputs composed of trolley motion, bridge motion, cargo hoisting displacement, and two cargo swing angles. Control of such a system is harder than full-actuator systems and meets many challenges. This part introduces the robust and adaptive control techniques applied for overhead cranes and the symbolic underactuated mechanical systems. Chapter 15 proposes a robust nonlin‐ ear controller integrating state observer by using Lyapunov-based design, in which controll‐ ability and observability are also investigated. Chapter 16 constitutes a distributed mass model of overhead crane with flexible handling cable and proposes two nonlinear control‐

control system for regulating the heart rate during treadmill exercises.

tainty and unknown disturbances.

X Preface

This book is formed by the recent studies of many authors around the world. As an editor, I would like to thank all the authors for their excellent contributions to the book. I am also sincerely grateful to Mr. Slobodan at IntechOpen who helped me to manage the editorial process positively and effectively. Hopefully, the readers will find many useful information and professional knowledge in this book.

#### **Le Anh Tuan**

Associate Professor at Automotive Engineering Department Vietnam Maritime University, Haiphong, Vietnam Research Professor at Center of Wind Energy System Kunsan National University, Gunsan, South Korea

**Section 1**

**Sliding Mode Based Controls**

**Sliding Mode Based Controls**

**Chapter 1**

Provisional chapter

**Robust Adaptive Controls of a Vehicle Seat Suspension**

DOI: 10.5772/intechopen.71422

This work proposes two novel adaptive fuzzy controllers and applies them to vibration control of a vehicle seat suspension system subjected to severe road profiles. The first adaptive controller is designed by considering prescribed performance of the sliding surface and combined with adaptation laws so that robust stability is guaranteed in the presence of external disturbances. As for the second adaptive controller, both the Hinfinity controller and sliding mode controller are combined using inversely fuzzified values of the fuzzy model. In order to evaluate control performances of the proposed two adaptive controllers, a semi-active vehicle suspension system installed with a magneto-rheological (MR) damper is adopted. After determining control gains, two controllers are applied to the system and vibration control performances such as displacement at the driver's position are evaluated and presented in time domain. In this work, to demonstrate the control robustness two severe road profiles of regular bump and random step wave are imposed as external disturbances. It is shown that both adaptive controllers can enhance ride comfort of the driver by reducing the displacement and acceleration at the seat position. This excellent performance is achieved from each benefit of each adaptive controller; accurate tracking performance of the first

Do Xuan Phu, Ta Duc Huy and Seung Bok Choi

Robust Adaptive Controls of a Vehicle Seat

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

controller and fast convergence time of the second controller.

Keywords: adaptive fuzzy control, sliding mode control, H-infinity control, prescribed performance of the sliding surface, vibration control, seat

Nowadays, modern control-based technical devices such as robotics, assistive machines and home appliances are popularly used to improve the level of human being's life. In these devices,

> © The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

http://dx.doi.org/10.5772/intechopen.71422

Do Xuan Phu, Ta Duc Huy and

Suspension System

**System**

Seung Bok Choi

Abstract

suspension system

1. Introduction

Provisional chapter
