Download or read book Performance Analysis of Non linear Adaptive Control Laws Using Hardware in the Loop of an Unmanned Aerial System written by Brendon Lyons and published by . This book was released on 2013 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: "In practical applications, an Unmanned Aerial System's (UAS) baseline performance is dictated by how well it can follow a given trajectory with limited stress on the actuators. However, these can be insufficient performance metrics when the UAS is allowed to adapt to an unpredicted external influence such as turbulence or actuation failure, while maintaining a satisfactory baseline performance. In this thesis, different control laws based on the formation flight geometry problem, nonlinear dynamic inversion and an artificial immune system adaptive mechanism, are implemented in hardware-in-the-loop as a precursor for in-flight testing. These controllers are compared based on three performance metrics: trajectory following, control activity and computer task execution time. The controllers chosen for comparison are: Basic Proportional-Integral-Derivative (PID), Outer loop Non-Linear Dynamic Inversion (NLDI), Extended NLDI, and the previous three controllers augmented with an AIS for a total of six controllers. The Extended NLDI augmented with the AIS outperformed all of the other algorithms under falure conditions on a global scale."--Leaf iii.

Download or read book International Aerospace Abstracts written by and published by . This book was released on 1999 with total page 1042 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonlinear Control of Fixed Wing UAVs with Time Varying and Unstructured Uncertainties written by Michail G. Michailidis and published by Springer Nature. This book was released on 2020-02-21 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a comprehensive and mathematically rigorous controller design for families of nonlinear systems with time-varying parameters and unstructured uncertainties. Although the presented methodology is general, the specific family of systems considered is the latest, NextGen, unconventional fixed-wing unmanned aircraft with circulation control or morphing wings, or a combination of both. The approach considers various sources of model and parameter uncertainty, while the controller design depends not on a nominal plant model, but instead on a family of admissible plants. In contrast to existing controller designs that consider multiple models and multiple controllers, the proposed approach is based on the ‘one controller fits all models’ within the unstructured uncertainty interval. The book presents a modeling-based analysis and synthesis approach with additive uncertainty weighting functions for accurate realization of the candidate systems. This differs significantly from existing designs in that it is capable of handling time-varying characteristics. This research monograph is suitable for scientists, engineers, researchers and graduate students with a background in control system theory who are interested in complex engineering nonlinear systems.

Download or read book Advanced Robust Nonlinear Control Approaches for Quadrotor Unmanned Aerial Vehicle written by Moussa Labbadi and published by Springer Nature. This book was released on 2021-09-14 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book studies selected advanced flight control schemes for an uncertain quadrotor unmanned aerial vehicle (UAV) systems in the presence of constant external disturbances, parametric uncertainties, measurement noise, time-varying external disturbances, and random external disturbances. Furthermore, in all the control techniques proposed in this book, it includes the simulation results with comparison to other nonlinear control schemes recently developed for the tracking control of a quadrotor UAV. The main contributions of the present book for quadrotor UAV systems are as follows: (i) the proposed control methods are based on the high-order sliding mode controller (SMC) and hybrid control algorithm with an optimization method. (ii) the finite-time control schemes are developed by using fast terminal SMC (FTSMC), nonsingular FTSMC (NFTSMC), global time-varying SMC, and adaptive laws. (iii) the fractional-order flight control schemes are developed by using the fractional-order calculus theory, super twisting algorithm, NFTSMC, and the SMC. This book covers the research history and importance of quadrotor system subject to system uncertainties, external wind disturbances, and noise measurements, as well as the research status of advanced flight control methods, adaptive flight control methods, and flight control based on fractional-order theory. The book would be interesting to most academic undergraduate, postgraduates, researchers on flight control for drones and applications of advanced controllers in engineering field. This book presents a must-survey for advanced finite-time control for quadrotor system. Some parts of this book have the potential of becoming the courses for the modelling and control of autonomous flying machines. Readers (academic researcher, undergraduate student, postgraduate student, MBA/executive, and education practitioner) interested in nonlinear control methods find this book an investigation. This book can be used as a good reference for the academic research on the control theory, drones, terminal sliding mode control, and related to this or used in Ph.D. study of control theory and their application in field engineering.

Download or read book Adaptive Control of Unmanned Aerial Systems written by Zachary Thompson Dydek and published by . This book was released on 2010 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive control is considered to be one of the key enabling technologies for future high-performance, safety-critical systems such as air-breathing hypersonic vehicles. Adaptive flight control systems offer improved performance and increased robustness to uncertainties by virtue of their ability to adjust control parameters as a function of online measurements. Extensive research in the field of adaptive control theory has enabled the design, analysis, and synthesis of stable adaptive systems. We are now entering the stage in which adaptive flight control systems have reached the requisite level of maturity for application to hardware flight platforms. Unmanned aerial systems (UAS) provide a unique opportunity for the transition of adaptive controllers from theory to practice. The small, unmanned aerial vehicles (UAVs) examined in this thesis offer a low-cost, low-risk stepping stone between simulation and application to higher-risk systems in which safety is a critical concern. Unmanned aircraft also offer several benefits over their manned counterparts including extreme persistence, maneuverability, lower weight and smaller size. Furthermore, several missions such as surveillance, exploration, search-and-track, and lifting of heavy loads are best accomplished by a UAS consisting of multiple UAVs. This thesis addresses some of the challenges involved with the application of adaptive flight control systems to UAS. Novel adaptive control architectures are developed to overcome performance limitations of UAS, the most significant of which is a large time delay due to communication and limited onboard processing. Analytical tools that allow the calculation of a theoretically justified time delay limit are also developed. These tools in turn lead to an estimate of the time-delay margin of the closed-loop system which is an essential part of the validation and verification methodology for intelligent flight control systems. These approaches are validated numerically using a series of simulation studies. These controllers and analytical methods are then applied to the UAV, demonstrating improved performance and increased robustness to time delays. Also introduced in this thesis is a novel adaptive methodology for coordinated adaptive control of a multi-vehicle UAS. Including two distinct classes of adaptive algorithms at both the local and global levels was found to result, both in simulation and in actual flight 3 tests, in decreased tracking error for individual vehicles, decreased errors in intervehicle distances, and reduced likelihood of collisions with other vehicles or obstacles in the environment.

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1989 with total page 1148 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligent Adaptive Control for Nonlinear Applications written by Shaaban Ali Salman Ali and published by . This book was released on 2008 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis deals with the design and implementation of an Adaptive Flight Control technique for Unmanned Aerial Vehicles (UAVs). The application of UAVs has been increasing exponentially in the last decade both in Military and Civilian fronts. These UAVs fly at very low speeds and Reynolds numbers, have nonlinear coupling, and tend to exhibit time varying characteristics. In addition, due to the variety of missions, they fly in uncertain environments exposing themselves to unpredictable external disturbances. The successful completion of the UAV missions is largely dependent on the accuracy of the control provided by the flight controllers. Thus there is a necessity for accurate and robust flight controllers. These controllers should be able to adapt to the changes in the dynamics due to internal and external changes. From the available literature, it is known that, one of the better suited adaptive controllers is the model based controller. The design and implementation of model based adaptive controller is discussed in the thesis. A critical issue in the design and application of model based control is the online identification of the UAV dynamics from the available sensors using the onboard processing capability. For this, proper instrumentation in terms of sensors and avionics for two platforms developed at UNSW@ADFA is discussed. Using the flight data from the remotely flown platforms, state space identification and fuzzy identification are developed to mimic the UAV dynamics. Real time validations using Hardware in Loop (HIL) simulations show that both the methods are feasible for control. A finer comparison showed that the accuracy of identification using fuzzy systems is better than the state space technique. The flight tests with real time online identification confirmed the feasibility of fuzzy identification for intelligent control. Hence two adaptive controllers based on the fuzzy identification are developed. The first adaptive controller is a hybrid indirect adaptive controller that utilises the model sensitivity in addition to output error for adaptation. The feedback of the model sensitivity function to adapt the parameters of the controller is shown to have beneficial effects, both in terms of convergence and accuracy. HIL simulations applied to the control of roll stabilised pitch autopilot for a typical UAV demonstrate the improvements compared to the direct adaptive controller. Next a novel fuzzy model based inversion controller is presented. The analytical approximate inversion proposed in this thesis does not increase the computational effort. The comparisons of this controller with other controller for a benchmark problem are presented using numerical simulations. The results bring out the superiority of this technique over other techniques. The extension of the analytical inversion based controller for multiple input multiple output problem is presented for the design of roll stabilised pitch autopilot for a UAV. The results of the HIL simulations are discussed for a typical UAV. Finally, flight test results for angle of attack control of one of the UAV platforms at UNSW@ADFA are presented. The flight test results show that the adaptive controller is capable of controlling the UAV suitably in a real environment, demonstrating its robustness characteristics.

Download or read book Robust Discrete Time Flight Control of UAV with External Disturbances written by Shuyi Shao and published by Springer Nature. This book was released on 2020-09-26 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book studies selected discrete-time flight control schemes for fixed-wing unmanned aerial vehicle (UAV) systems in the presence of system uncertainties, external disturbances and input saturation. The main contributions of this book for UAV systems are as follows: (i) the proposed integer-order discrete-time control schemes are based on the designed discrete-time disturbance observers (DTDOs) and the neural network (NN); and (ii) the fractional-order discrete-time control schemes are developed by using the fractional-order calculus theory, the NN and the DTDOs. The book offers readers a good understanding of how to establish discrete-time tracking control schemes for fixed-wing UAV systems subject to system uncertainties, external wind disturbances and input saturation. It represents a valuable reference guide for academic research on uncertain UAV systems, and can also support advanced / Ph.D. studies on control theory and engineering.

Download or read book Design of Control Laws and State Observers for Fixed Wing UAVs written by Arturo Tadeo Espinoza-Fraire and published by Elsevier. This book was released on 2022-09-29 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design of Control Laws and State Observers for Fixed-Wing UAVs: Simulation and Experimental Approaches provides readers with modeling techniques, simulations, and results from real-time experiments using linear and nonlinear controllers and state observers. The book starts with an overview of the history of UAVs and the equations of motion applied to them. Following chapters analyze linear and nonlinear controllers, state observers, and the book concludes with a chapter discussing testbed development and experimental results, equipping readers with the knowledge they need to conduct their own stable UAV flights whether in simulation or real-time. - Presents aerodynamic models for fixed-wing UAVs that can be used to design control laws and state observers - Applies linear and nonlinear control theories and state observers to fixed-wing UAVs - Provides real-time flight and simulation test results of fixed-wing UAVs with linear and nonlinear controllers

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1989 with total page 1148 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book L1 Adaptive Control Theory written by Naira Hovakimyan and published by SIAM. This book was released on 2010-09-30 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains results not yet published in technical journals and conference proceedings.

Download or read book Development of Fault Tolerant Adaptive Control Laws for Aerospace Systems written by Andres E. Perez Rocha and published by . This book was released on 2016 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main topic of this dissertation is the design, development and implementation of intelligent adaptive control techniques designed to maintain healthy performance of aerospace systems subjected to malfunctions, external parameter changes and/or unmodeled dynamics. The dissertation is focused on the development of novel adaptive control configurations that rely on non-linear functions that appear in the immune system of living organisms as main source of adaptation. One of the main goals of this dissertation is to demonstrate that these novel adaptive control architectures are able to improve overall performance and protect the system while reducing control effort and maintaining adequate operation outside bounds of nominal design. This research effort explores several phases, ranging from theoretical stability analysis, simulation and hardware implementation on different types of aerospace systems including spacecraft, aircraft and quadrotor vehicles. The results presented in this dissertation are focused on two main adaptivity approaches, the first one is intended for aerospace systems that do not attain large angles and use exact feedback linearization of Euler angle kinematics. A proof of stability is presented by means of the circle Criterion and Lyapunov's direct method. The second approach is intended for aerospace systems that can attain large attitude angles (e.g. space systems in gravity-less environments), the adaptation is incorporated on a baseline architecture that uses partial feedback linearization of quaternions kinematics. In this case, the closed loop stability was analyzed using Lyapunov's direct method and Barbalat's Lemma. It is expected that some results presented in this dissertation can contribute towards the validation and certification of direct adaptive controllers.

Download or read book Fault tolerant Flight Control and Guidance Systems written by Guillaume J. J. Ducard and published by Springer Science & Business Media. This book was released on 2009-05-14 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a complete overview of fault-tolerant flight control techniques. Discussion covers the necessary equations for the modeling of small UAVs, a complete system based on extended Kalman filters, and a nonlinear flight control and guidance system.

Download or read book Fully Tuned Radial Basis Function Neural Networks for Flight Control written by N. Sundararajan and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.

Download or read book Nonlinear Control of Robots and Unmanned Aerial Vehicles written by Ranjan Vepa and published by CRC Press. This book was released on 2016-10-14 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Control of Robots and Unmanned Aerial Vehicles: An Integrated Approach presents control and regulation methods that rely upon feedback linearization techniques. Both robot manipulators and UAVs employ operating regimes with large magnitudes of state and control variables, making such an approach vital for their control systems design. Numerous application examples are included to facilitate the art of nonlinear control system design, for both robotic systems and UAVs, in a single unified framework. MATLAB® and Simulink® are integrated to demonstrate the importance of computational methods and systems simulation in this process.

Download or read book Neural Network Based Adaptive Control for Autonomous Flight of Fixed Wing Unmanned Aerial Vehicles written by Vishwas Ramadas Puttige and published by . This book was released on 2009 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents the development of small, inexpensive unmanned aerial vehicles (UAVs) to achieve autonomous fight. Fixed wing hobby model planes are modified and instrumented to form experimental platforms. Different sensors employed to collect the flight data are discussed along with their calibrations. The time constant and delay for the servo-actuators for the platform are estimated. Two different data collection and processing units based on micro-controller and PC104 architectures are developed and discussed. These units are also used to program the identification and control algorithms. Flight control of fixed wing UAVs is a challenging task due to the coupled, time-varying, nonlinear dynamic behaviour. One of the possible alternatives for the flight control system is to use the intelligent adaptive control techniques that provide online learning capability to cope with varying dynamics and disturbances. Neural network based indirect adaptive control strategy is applied for the current work. The two main components of the adaptive control technique are the identification block and the control block. Identification provides a mathematical model for the controller to adapt to varying dynamics. Neural network based identification provides a black-box identification technique wherein a suitable network provides prediction capability based upon the past inputs and outputs. Auto-regressive neural networks are employed for this to ensure good retention capabilities for the model that uses the past outputs and inputs along with the present inputs. Online and offline identification of UAV platforms are discussed based upon the flight data. Suitable modifications to the Levenberg-Marquardt training algorithm for online training are proposed. The effect of varying the different network parameters on the performance of the network are numerically tested out. A new performance index is proposed that is shown to improve the accuracy of prediction and also reduces the training time for these networks. The identification algorithms are validated both numerically and flight tested. A hardware-in-loop simulation system has been developed to test the identification and control algorithms before flight testing to identify the problems in real time implementation on the UAVs. This is developed to keep the validation process simple and a graphical user interface is provided to visualise the UAV flight during simulations. A dual neural network controller is proposed as the adaptive controller based upon the identification models. This has two neural networks collated together. One of the neural networks is trained online to adapt to changes in the dynamics. Two feedback loops are provided as part of the overall structure that is seen to improve the accuracy. Proofs for stability analysis in the form of convergence of the identifier and controller networks based on Lyapunov's technique are presented. In this analysis suitable bounds on the rate of learning for the networks are imposed. Numerical results are presented to validate the adaptive controller for single-input single-output as well as multi-input multi-output subsystems of the UAV. Real time validation results and various flight test results confirm the feasibility of the proposed adaptive technique as a reliable tool to achieve autonomous flight. The comparison of the proposed technique with a baseline gain scheduled controller both in numerical simulations as well as test flights bring out the salient adaptive feature of the proposed technique to the time-varying, nonlinear dynamics of the UAV platforms under different flying conditions.

Download or read book Robust and Adaptive Nonlinear Control of Limit Cycle Oscillations in UAVs Using Synthetic Jet Actuators written by Natalie Ramos Pedroza and published by . This book was released on 2014 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, three nonlinear SJS-based control approaches are presented, which are capable of complete (i.e., asymptotic) suppression of LCO in UAV systems containing uncertainty. An adaptive control method is presented first, which is shown to achieve asymptotic regulation of LCO for UAVs in the presence of model uncertainty and unmodelled external disturbances. Motivated by the desire to reduce the computational complexity of the closed-loop system, a structurally simplistic robust (single feedback loop) control design is presented next, which is shown to achieve asymptotoc LCO regulation without the need for adaptive parameter estimation. Finally, to address the control challenges encountered in the event of actuator faults, a robust control method is presented for this underactuared scenario is also proven to completely compensate for the inherent SJA nonlinearity. Rigourous Lyapunov-based stability analyses are provided to prove the theoretical results, and numerical simulation results are provided to complement the theoretical development.