The Experts below are selected from a list of 252 Experts worldwide ranked by ideXlab platform

Ioannis A Raptis - One of the best experts on this subject based on the ideXlab platform.

  • linear tracking control for small scale unmanned Helicopters
    IEEE Transactions on Control Systems and Technology, 2012
    Co-Authors: Ioannis A Raptis, Kimon P Valavanis, George Vachtsevanos
    Abstract:

    This paper presents a model-based tracking control design for small-scale unmanned Helicopters. The design objective is for the helicopter to track predefined inertial position (or velocity) and heading reference trajectories. The controller is based on a nominal linear state-space model that successfully captures the small-scale helicopter coupled multivariable dynamics. The flight controller is composed of two feedback loops that regulate the tracking error of the longitudinal-lateral and heading-heave motion of the helicopter, respectively. The tracking error is determined by constructing a reference state generator based on the linear helicopter model and the reference outputs. The state generator can be systematically designed using the backstepping approach for systems in feedback form and by applying a physically meaningful approximation to the linear helicopter model. The controller performance is successfully tested using a realistic flight simulator.

  • a novel nonlinear backstepping controller design for Helicopters using the rotation matrix
    IEEE Transactions on Control Systems and Technology, 2011
    Co-Authors: Ioannis A Raptis, Kimon P Valavanis, Wilfrido Moreno
    Abstract:

    This brief presents a backstepping controller design for Helicopters. The controller objective is for the helicopter to autonomously track predefined position and yaw reference trajectories. The incorporation of nested saturation feedback functions in the backstepping design preserves the helicopter's motion and power physical constraints. The intermediate control signals related to the attitude dynamics exploit the structural properties of the rotation matrix and are enhanced with terms that guarantee that the helicopter will not overturn while tracking the desired position trajectory. The attitude dynamics are rendered exponentially stable while the translational dynamics are globally asymptotically stable. Numerical simulations illustrate the applicability of the proposed design.

  • linear and nonlinear control of small scale unmanned Helicopters
    2010
    Co-Authors: Ioannis A Raptis, Kimon P Valavanis
    Abstract:

    1 Introduction.- 1.1 Background Information.- 1.2 The Mathematical Problem ..- 1.3 Controller Designs.- 1.3.1 Linear Controller Design.- 1.3.2 Nonlinear Controller Design.- 1.4 Outline of the Book.- 2 Review of Linear and Nonlinear Controller Designs.- 2.1 Linear Controller Designs.- 2.2 Nonlinear Controller Design.- 2.3 Remarks.- 3 Helicopter Basic Equations of Motion.- 3.1 Helicopter Equations of Motion.- 3.2 Position and Orientation of the Helicopter.- 3.2.1 Helicopter Position Dynamics.- 3.2.2 Helicopter Orientation Dynamics.- 3.3 Complete Helicopter Dynamics.- 3.4 Remarks.- 4 Simplified Rotor Dynamics.- 4.1 Introduction.- 4.2 Blade Motion.- 4.3 Swashplate Mechanism.- 4.4 Fundamental Rotor Aerodynamics.- 4.5 Flapping Equations of Motion.- 4.6 Rotor Tip-Path-Plane Equation.- 4.7 First Order Tip-Path-Plane Equations.- 4.8 Main Rotor Forces and Moments.- 4.9 Remarks.- 5 Frequency Domain System Identification.- 5.1 Mathematical Modeling.- 5.1.1 First Principles Modeling.- 5.1.2 System Identification Modeling.- 5.2 Frequency Domain System Identification.- 5.3 Advantages of the Frequency Domain Identification.- 5.4 Helicopter Identification Challenges.- 5.5 Frequency Response and the Coherence Function.- 5.6 The CIFER c Package.- 5.7 Time History Data and Excitation Inputs.- 5.8 Linearization of the Equations of Motion.- 5.9 Stability and Control Derivatives.- 5.10 Model Identification.- 5.10.1 Experimental Platform.- 5.10.2 Parametrized State Space Model.- 5.10.3 Identification Setup.- 5.10.4 Time Domain Validation.- 5.11 Remarks.- 6 Linear Tracking Controller Design for Small-Scale Unmanned Helicopters.- 6.1 Helicopter Linear Model.- 6.2 Linear Controller Design Outline.- 6.3 Decomposing the System.- 6.4 Velocity and Heading Tracking Controller Design.- 6.4.1 Lateral-Longitudinal Dynamics.- 6.4.2 Yaw-Heave Dynamics.- 6.4.3 Stability of the Complete System Error Dynamics.- 6.5 Position and Heading Tracking.- 6.6 PID Controller Design.- 6.7 Experimental Results.- 6.8 Remarks.- 7 Nonlinear Tracking Controller Design for Unmanned Helicopters.- 7.1 Introduction.- 7.2 Helicopter Nonlinear Model.- 7.2.1 Rigid Body Dynamics.- 7.2.2 ExternalWrench Model.- 7.2.3 Complete Rigid Body Dynamics.- 7.3 Translational Error Dynamics.- 7.4 Attitude Error Dynamics.- 7.4.1 Yaw Error Dynamics.- 7.4.2 Orientation Error Dynamics.- 7.4.3 Angular Velocity Error Dynamics.- 7.5 Stability of the Attitude Error Dynamics.- 7.6 Stability of the Translational Error Dynamics.- 7.7 Numeric Simulation Results.- 7.8 Remarks.- 8 Time Domain Parameter Estimation and Applied Discrete Nonlinear Control for Small-Scale Unmanned Helicopters.- 8.1 Introduction.- 8.2 Discrete System Dynamics.- 8.3 Discrete Backstepping Algorithm.- 8.3.1 Angular Velocity Dynamics.- 8.3.2 Translational Dynamics.- 8.3.3 Yaw Dynamics.- 8.4 Parameter Estimation Using Recursive Least Squares.- 8.5 Parametric Model.- 8.6 Experimental Results.- 8.6.1 Time History Data and Excitation Inputs.- 8.6.2 Validation.- 8.6.3 Control Design.- 8.7 Remarks.- 9 Time Domain System Identification for Small-Scale Unmanned Helicopters Using Fuzzy Models.- 9.1 Introduction.- 9.2 Takagi-Sugeno Fuzzy Models.- 9.3 Proposed Takagi-Sugeno System for Helicopters.- 9.4 Experimental Results.- 9.4.1 Tunning of the Membership Function Parameters.- 9.4.2 Validation.- 10 Comparison Studies.- 10.1 Summary of the Controller Designs.- 10.2 Experimental Results.- 10.3 First Maneuver: Forward Flight.- 10.4 Second Maneuver: Aggressive Forward Flight.- 10.5 Third Maneuver: 8 Shaped Trajectory.- 10.6 Fourth Maneuver: Pirouette Trajectory.- 10.7 Remarks.- 11 Epilogue.- 11.1 Introduction.- 11.2 Advantages and Novelties of the Designs.- 11.3 Testing and Implementation.- 11.4 Remarks.- A Fundamentals of Backstepping Control.- A.1 Integrator Backstepping.- A.2 Example of a Recursive Backstepping Design.- References.

Kimon P Valavanis - One of the best experts on this subject based on the ideXlab platform.

  • linear tracking control for small scale unmanned Helicopters
    IEEE Transactions on Control Systems and Technology, 2012
    Co-Authors: Ioannis A Raptis, Kimon P Valavanis, George Vachtsevanos
    Abstract:

    This paper presents a model-based tracking control design for small-scale unmanned Helicopters. The design objective is for the helicopter to track predefined inertial position (or velocity) and heading reference trajectories. The controller is based on a nominal linear state-space model that successfully captures the small-scale helicopter coupled multivariable dynamics. The flight controller is composed of two feedback loops that regulate the tracking error of the longitudinal-lateral and heading-heave motion of the helicopter, respectively. The tracking error is determined by constructing a reference state generator based on the linear helicopter model and the reference outputs. The state generator can be systematically designed using the backstepping approach for systems in feedback form and by applying a physically meaningful approximation to the linear helicopter model. The controller performance is successfully tested using a realistic flight simulator.

  • a novel nonlinear backstepping controller design for Helicopters using the rotation matrix
    IEEE Transactions on Control Systems and Technology, 2011
    Co-Authors: Ioannis A Raptis, Kimon P Valavanis, Wilfrido Moreno
    Abstract:

    This brief presents a backstepping controller design for Helicopters. The controller objective is for the helicopter to autonomously track predefined position and yaw reference trajectories. The incorporation of nested saturation feedback functions in the backstepping design preserves the helicopter's motion and power physical constraints. The intermediate control signals related to the attitude dynamics exploit the structural properties of the rotation matrix and are enhanced with terms that guarantee that the helicopter will not overturn while tracking the desired position trajectory. The attitude dynamics are rendered exponentially stable while the translational dynamics are globally asymptotically stable. Numerical simulations illustrate the applicability of the proposed design.

  • linear and nonlinear control of small scale unmanned Helicopters
    2010
    Co-Authors: Ioannis A Raptis, Kimon P Valavanis
    Abstract:

    1 Introduction.- 1.1 Background Information.- 1.2 The Mathematical Problem ..- 1.3 Controller Designs.- 1.3.1 Linear Controller Design.- 1.3.2 Nonlinear Controller Design.- 1.4 Outline of the Book.- 2 Review of Linear and Nonlinear Controller Designs.- 2.1 Linear Controller Designs.- 2.2 Nonlinear Controller Design.- 2.3 Remarks.- 3 Helicopter Basic Equations of Motion.- 3.1 Helicopter Equations of Motion.- 3.2 Position and Orientation of the Helicopter.- 3.2.1 Helicopter Position Dynamics.- 3.2.2 Helicopter Orientation Dynamics.- 3.3 Complete Helicopter Dynamics.- 3.4 Remarks.- 4 Simplified Rotor Dynamics.- 4.1 Introduction.- 4.2 Blade Motion.- 4.3 Swashplate Mechanism.- 4.4 Fundamental Rotor Aerodynamics.- 4.5 Flapping Equations of Motion.- 4.6 Rotor Tip-Path-Plane Equation.- 4.7 First Order Tip-Path-Plane Equations.- 4.8 Main Rotor Forces and Moments.- 4.9 Remarks.- 5 Frequency Domain System Identification.- 5.1 Mathematical Modeling.- 5.1.1 First Principles Modeling.- 5.1.2 System Identification Modeling.- 5.2 Frequency Domain System Identification.- 5.3 Advantages of the Frequency Domain Identification.- 5.4 Helicopter Identification Challenges.- 5.5 Frequency Response and the Coherence Function.- 5.6 The CIFER c Package.- 5.7 Time History Data and Excitation Inputs.- 5.8 Linearization of the Equations of Motion.- 5.9 Stability and Control Derivatives.- 5.10 Model Identification.- 5.10.1 Experimental Platform.- 5.10.2 Parametrized State Space Model.- 5.10.3 Identification Setup.- 5.10.4 Time Domain Validation.- 5.11 Remarks.- 6 Linear Tracking Controller Design for Small-Scale Unmanned Helicopters.- 6.1 Helicopter Linear Model.- 6.2 Linear Controller Design Outline.- 6.3 Decomposing the System.- 6.4 Velocity and Heading Tracking Controller Design.- 6.4.1 Lateral-Longitudinal Dynamics.- 6.4.2 Yaw-Heave Dynamics.- 6.4.3 Stability of the Complete System Error Dynamics.- 6.5 Position and Heading Tracking.- 6.6 PID Controller Design.- 6.7 Experimental Results.- 6.8 Remarks.- 7 Nonlinear Tracking Controller Design for Unmanned Helicopters.- 7.1 Introduction.- 7.2 Helicopter Nonlinear Model.- 7.2.1 Rigid Body Dynamics.- 7.2.2 ExternalWrench Model.- 7.2.3 Complete Rigid Body Dynamics.- 7.3 Translational Error Dynamics.- 7.4 Attitude Error Dynamics.- 7.4.1 Yaw Error Dynamics.- 7.4.2 Orientation Error Dynamics.- 7.4.3 Angular Velocity Error Dynamics.- 7.5 Stability of the Attitude Error Dynamics.- 7.6 Stability of the Translational Error Dynamics.- 7.7 Numeric Simulation Results.- 7.8 Remarks.- 8 Time Domain Parameter Estimation and Applied Discrete Nonlinear Control for Small-Scale Unmanned Helicopters.- 8.1 Introduction.- 8.2 Discrete System Dynamics.- 8.3 Discrete Backstepping Algorithm.- 8.3.1 Angular Velocity Dynamics.- 8.3.2 Translational Dynamics.- 8.3.3 Yaw Dynamics.- 8.4 Parameter Estimation Using Recursive Least Squares.- 8.5 Parametric Model.- 8.6 Experimental Results.- 8.6.1 Time History Data and Excitation Inputs.- 8.6.2 Validation.- 8.6.3 Control Design.- 8.7 Remarks.- 9 Time Domain System Identification for Small-Scale Unmanned Helicopters Using Fuzzy Models.- 9.1 Introduction.- 9.2 Takagi-Sugeno Fuzzy Models.- 9.3 Proposed Takagi-Sugeno System for Helicopters.- 9.4 Experimental Results.- 9.4.1 Tunning of the Membership Function Parameters.- 9.4.2 Validation.- 10 Comparison Studies.- 10.1 Summary of the Controller Designs.- 10.2 Experimental Results.- 10.3 First Maneuver: Forward Flight.- 10.4 Second Maneuver: Aggressive Forward Flight.- 10.5 Third Maneuver: 8 Shaped Trajectory.- 10.6 Fourth Maneuver: Pirouette Trajectory.- 10.7 Remarks.- 11 Epilogue.- 11.1 Introduction.- 11.2 Advantages and Novelties of the Designs.- 11.3 Testing and Implementation.- 11.4 Remarks.- A Fundamentals of Backstepping Control.- A.1 Integrator Backstepping.- A.2 Example of a Recursive Backstepping Design.- References.

Jianda Han - One of the best experts on this subject based on the ideXlab platform.

  • A Review on Fault Diagnosis and Fault Tolerant Control Methods for Single-rotor Aerial Vehicles
    Journal of Intelligent & Robotic Systems, 2014
    Co-Authors: Xin Qi, Jianda Han, Juntong Qi, Didier Theilliol, Dalei Song, Youmin Zhang, ChunSheng Hua
    Abstract:

    Faults or failures are inevitable to occur and their prompt detection and isolation are essential for the dependability of various systems and for avoiding damages to the system itself, persons and the environment. Therefore, the safety of helicopter platforms have attracted the attention of many researchers in the past two decades. In order to deal with these problems, this paper presents an overview of the recent development and current researches in the field of fault diagnosis, including analytical/model-based, signal processing-based and knowledge-based techniques, and also passive/active fault- tolerant control approaches. Among various Helicopters, single-rotor aerial vehicles, i.e. manned Helicopters, unmanned Helicopters, two and three degree-of-freedom unmanned helicopter experimental platforms, are considered for providing an overall picture of the fault diagnosis and fault-tolerant control approaches based on the review of journal articles in last two decades, conference articles in last several years and some books.

  • Fault diagnosis and fault tolerant control methods for manned and unmanned Helicopters: a literature review
    2013
    Co-Authors: Didier Theilliol, Jianda Han, Dalei Song, Youmin Zhang, Ling Wang, Yong Xia
    Abstract:

    With the development of unmanned Helicopters, the dependability of Helicopters have attracted more and more attention of many researchers. In order to deal with these problems, fault diagnosis and fault tolerant control methods were used for manned or unmanned helicopter platforms. This paper presents an overview of the existing works on fault diagnosis, including analytical/model-based, signal processing-based and knowledge-based techniques, and passive/active fault tolerant control approaches for Helicopters mainly with single rotor. Before the main part of the review, a short description of fault classification is presented. Compared with the former work, this review contains some in-depth discussion of various fault diagnosis techniques and a survey for fault tolerant control methods.

  • a literature review on fault diagnosis methods for manned and unmanned Helicopters
    International Conference on Unmanned Aircraft Systems, 2013
    Co-Authors: Didier Theilliol, Youmin Zhang, Jianda Han
    Abstract:

    In the past two decades, the reliability and safety of Helicopters have attracted the attention of many researchers. Especially with the development of Unmanned Helicopters, Fault Diagnosis approaches were used for manned or unmanned helicopter platforms. In this paper, a brief state-of-the-art on Fault Diagnosis approaches is presented for Helicopters, including analytical model-based, signal processing-based and knowledge-based Fault Diagnosis approaches. A short description of fault types is presented before the main part of the review.

Didier Theilliol - One of the best experts on this subject based on the ideXlab platform.

  • A Review on Fault Diagnosis and Fault Tolerant Control Methods for Single-rotor Aerial Vehicles
    Journal of Intelligent & Robotic Systems, 2014
    Co-Authors: Xin Qi, Jianda Han, Juntong Qi, Didier Theilliol, Dalei Song, Youmin Zhang, ChunSheng Hua
    Abstract:

    Faults or failures are inevitable to occur and their prompt detection and isolation are essential for the dependability of various systems and for avoiding damages to the system itself, persons and the environment. Therefore, the safety of helicopter platforms have attracted the attention of many researchers in the past two decades. In order to deal with these problems, this paper presents an overview of the recent development and current researches in the field of fault diagnosis, including analytical/model-based, signal processing-based and knowledge-based techniques, and also passive/active fault- tolerant control approaches. Among various Helicopters, single-rotor aerial vehicles, i.e. manned Helicopters, unmanned Helicopters, two and three degree-of-freedom unmanned helicopter experimental platforms, are considered for providing an overall picture of the fault diagnosis and fault-tolerant control approaches based on the review of journal articles in last two decades, conference articles in last several years and some books.

  • Fault diagnosis and fault tolerant control methods for manned and unmanned Helicopters: a literature review
    2013
    Co-Authors: Didier Theilliol, Jianda Han, Dalei Song, Youmin Zhang, Ling Wang, Yong Xia
    Abstract:

    With the development of unmanned Helicopters, the dependability of Helicopters have attracted more and more attention of many researchers. In order to deal with these problems, fault diagnosis and fault tolerant control methods were used for manned or unmanned helicopter platforms. This paper presents an overview of the existing works on fault diagnosis, including analytical/model-based, signal processing-based and knowledge-based techniques, and passive/active fault tolerant control approaches for Helicopters mainly with single rotor. Before the main part of the review, a short description of fault classification is presented. Compared with the former work, this review contains some in-depth discussion of various fault diagnosis techniques and a survey for fault tolerant control methods.

  • a literature review on fault diagnosis methods for manned and unmanned Helicopters
    International Conference on Unmanned Aircraft Systems, 2013
    Co-Authors: Didier Theilliol, Youmin Zhang, Jianda Han
    Abstract:

    In the past two decades, the reliability and safety of Helicopters have attracted the attention of many researchers. Especially with the development of Unmanned Helicopters, Fault Diagnosis approaches were used for manned or unmanned helicopter platforms. In this paper, a brief state-of-the-art on Fault Diagnosis approaches is presented for Helicopters, including analytical model-based, signal processing-based and knowledge-based Fault Diagnosis approaches. A short description of fault types is presented before the main part of the review.

Rogelio Lozano - One of the best experts on this subject based on the ideXlab platform.

  • Lagrangian helicopter model
    Non-linear Control for Underactuated Mechanical Systems, 2002
    Co-Authors: Isabelle Fantoni, Rogelio Lozano
    Abstract:

    There is a growing interest in the construction and control of autonomous model Helicopters [47, 90]. Recently, a number of authors from the control community have begun to investigate an integrated non-linear dynamic model of a scale model autonomous helicopter (cf. conference papers [28, 62, 95, 101, 119] and more recently the jounal papers [93, 102]). Model Helicopters display a considerably different dynamic response than full scale Helicopters. For example, the classical model [87, pg. 557] used for a full size helicopter does not model the interaction of the rotor blade dynamics with the rigid body dynamics of the airframe. Instead, the rotor blade dynamics are incorporated into the modelling of a daunting collection of aerodynamic and parasitic forces, which in turn act on the rigid body dynamics. It appears from experience that the regulation of the rotor speed of a model helicopter is an important part of the integrated control problem [118].

  • Nonlinear control of Helicopters
    2001 European Control Conference (ECC), 2001
    Co-Authors: Juan Carlos Avila Vilchis, Bernard Brogliato, Rogelio Lozano
    Abstract:

    This work focuses on the nonlinear control of Helicopters. Our global interest is a general model (7-DOF) to be used on the autonomous forward-flight of Helicopters. However, in this paper we present a reduced-order model (3-DOF) representing a scale model helicopter mounted on an experimental platform. In this system the vertical flight of the helicopter can be studied. Although simplified, this 3-DOF Lagrangian model presents quite interesting control challenges due to nonlinearities, aerodynamical forces and underactuation. Due to the very particular dynamical and control properties of the 3-DOF model we propose a specific nonlinear controller using passivity properties to control the rotational part of the system. An I/O linearizing controller is used for the helicopter altitude control. Numerical simulations are presented to illustrate the performance of these controllers.