Download or read book Fast Nonlinear Model Predictive Control of Quadrotors written by Hadi Mohammadi Daniali and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Quadrotor (or quadcopter) is a type of Unmanned Aerial Vehicles (UAVs). Due to the quadrotors simple and inexpensive design, they have become popular platforms. This thesis proposes a computationally fast scheme for implementing Nonlinear Model Predictive Control (NMPC) as a high-level controller to solve the path following problem for unmanned quadrotors. After discussing the background and reviewing the literature, it is noted that this problem referred widely in the literature as a necessary step toward the autonomous flight of quadrotor UAVs. The previous studies usually used simplified models which are computationally uncomplicated and straightforward in terms of control developments and stability investigations. Moreover, some articles are presented showing the importance of accurate state observation on the performance of feedback-based control approaches. The NMPC-based controller is designed using a more realistic highly nonlinear control-oriented model which requires heavy computations for practical real-time implementations. To deal with this issue, the Newton generalized minimal residual (Newton/GMRES) method is applied to solve the NMPC's real-time optimizations rapidly during the control process. This technique uses the Hamiltonian method to derive a set of equations with multiple variables. To solve these in a real-time application, the Newton/GMRES method applies forward-difference generalized minimal residual (fdgmres) algorithm. The simulation and experimental result using a commercial drone, called AR.Drone 2.0, in our laboratory instrumented by a Vicon Vantage motion capture system, demonstrate that our feedback-based control method's performance highly depends on the reliability of the state vector feedback signals. As a result, a Kalman filter and Luenberger observer algorithms are used for estimating unknown states. The NMPC-based controller operation is simulated, and the result reveals the similar efficiency of observers. Moreover, the NMPC control approach is compared with a proportional controller which shows great improvements in the response of the quadrotor. The experiment showed that our control method is sufficiently fast for practical implementations, and it can solve the trajectory tracking problem properly even for complex paths. This thesis is concluded by stating a summary of contributions and some potential future works.

Download or read book Nonlinear Model Predictive Control of a Quadrotor written by Emilio Melgarejo Hernández and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most important features of a quadrotor in order to properly work, generally in some sort of path tracking, is to have a suitable control. This thesis will approach the problem of controlling a quadrotor applying the control technique known as Nonlinear Model Predictive Control. First, this control should guarantee stability and feasibility, and then the control parameters are tuned to obtain the better possible performance. Proper simulations will be performed by selecting different situations in terms of path tracking references, as well as in terms of the accuracy level of the control model with respect to the real system represented by a high-fidelity model. Additionally, the requirements for the controller to work in real time will be explored and discussed.

Download or read book Assessment and Future Directions of Nonlinear Model Predictive Control written by Rolf Findeisen and published by Springer. This book was released on 2007-09-08 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.

Download or read book Nonlinear Model Predictive Control and Its Applications to a Fast Mechanical System written by Gokhan Mehmet Atinc and published by . This book was released on 2009 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Model Predictive Control written by Saša V. Raković and published by Springer. This book was released on 2018-09-01 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using “computationally intensive controls,” so the second part of this book addresses the solution of optimization problems in “real” time for model-predictive control. The theory and applications of control theory often influence each other, so the last section of Handbook of Model Predictive Control rounds out the book with representative applications to automobiles, healthcare, robotics, and finance. The chapters in this volume will be useful to working engineers, scientists, and mathematicians, as well as students and faculty interested in the progression of control theory. Future developments in MPC will no doubt build from concepts demonstrated in this book and anyone with an interest in MPC will find fruitful information and suggestions for additional reading.

Download or read book Non linear Predictive Control written by Basil Kouvaritakis and published by Institution of Engineering & Technology. This book was released on 2001-10-26 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advantage of model predictive control is that it can take systematic account of constraints, thereby allowing processes to operate at the limits of achievable performance. Engineers in academia, industry, and government from the US and Europe explain how the linear version can be adapted and applied to the nonlinear conditions that characterize the dynamics of most real manufacturing plants. They survey theoretical and practical trends, describe some specific theories and demonstrate their practical application, derive strategies that provide appropriate assurance of closed-loop stability, and discuss practical implementation. Annotation copyrighted by Book News, Inc., Portland, OR

Download or read book Proceedings of 2022 International Conference on Autonomous Unmanned Systems ICAUS 2022 written by Wenxing Fu and published by Springer Nature. This book was released on 2023-03-10 with total page 3985 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original, peer-reviewed research papers from the ICAUS 2022, which offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas. The aim of the ICAUS 2022 is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The topics covered include but are not limited to Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and Its Application in Unmanned Systems. The papers showcased here share the latest findings on Unmanned Systems, Robotics, Automation, Intelligent Systems, Control Systems, Integrated Networks, Modeling and Simulation. It makes the book a valuable asset for researchers, engineers, and university students alike.

Download or read book Mobile Robot Motion Control and Path Planning written by Ahmad Taher Azar and published by Springer Nature. This book was released on 2023-06-30 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the recent research advances in linear and nonlinear control techniques. From both a theoretical and practical standpoint, motion planning and related control challenges are key parts of robotics. Indeed, the literature on the planning of geometric paths and the generation of time-based trajectories, while accounting for the compatibility of such paths and trajectories with the kinematic and dynamic constraints of a manipulator or a mobile vehicle, is extensive and rich in historical references. Path planning is vital and critical for many different types of robotics, including autonomous vehicles, multiple robots, and robot arms. In the case of multiple robot route planning, it is critical to produce a safe path that avoids colliding with objects or other robots. When designing a safe path for an aerial or underwater robot, the 3D environment must be considered. As the number of degrees of freedom on a robot arm increases, so does the difficulty of path planning. As a result, safe pathways for high-dimensional systems must be developed in a timely manner. Nonetheless, modern robotic applications, particularly those requiring one or more robots to operate in a dynamic environment (e.g., human–robot collaboration and physical interaction, surveillance, or exploration of unknown spaces with mobile agents, etc.), pose new and exciting challenges to researchers and practitioners. For instance, planning a robot's motion in a dynamic environment necessitates the real-time and online execution of difficult computational operations. The development of efficient solutions for such real-time computations, which could be offered by specially designed computational architectures, optimized algorithms, and other unique contributions, is thus a critical step in the advancement of present and future-oriented robotics.

Download or read book Nonlinear Model Predictive Control written by Valentino Razza and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Model Based Predictive Control written by J.A. Rossiter and published by CRC Press. This book was released on 2017-07-12 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications. This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.

Download or read book Gradient based Nonlinear Model Predictive Control with Constraint Transformation for Fast Dynamical Systems written by Bartosz Maciej Käpernick and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Trajectory Generation and Constrained Control of Quadrotors written by Carlos Alberto Tule and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Systems, although still in early development, are expected to grow in both the military and civil sectors. As part of the UAV sector, the Quadrotor helicopter platform has been receiving a lot of interest from various academic and research institutions because of their simplistic design and low cost to manufacture, yet remaining a challenging platform to control. Four different controllers were derived for the trajectory generation and constrained control of a quadrotor platform. The first approach involves the linear version of the Model predictive Control (MPC) algorithm to solve the state constrained optimization problem. The second appraoch uses the State Dependent Coefficient (SDC) form to capture the system non linearities into a pseudo-linear system matrix, which is used to derive the State Dependent Riccati Equation (SDRE) based optimal control. For the third approach, the SDC form is exploited for obtaining a nonlinear equivalent of the model predictive control. Lastly, a combination of the nonlinear MPC and SDRE optimal control algorithms is used to explor the feasibility of a near real-time nonlinear optimization technique.

Download or read book Robotics Research written by Nancy M. Amato and published by Springer Nature. This book was released on 2019-11-28 with total page 1058 pages. Available in PDF, EPUB and Kindle. Book excerpt: ISRR, the "International Symposium on Robotics Research", is one of robotics pioneering Symposia, which has established over the past two decades some of the field's most fundamental and lasting contributions. This book presents the results of the eighteenth edition of "Robotics Research" ISRR17, offering a collection of a broad range of topics in robotics. This symposium took place in Puerto Varas, Chile from December 11th to December 14th, 2017. The content of the contributions provides a wide coverage of the current state of robotics research, the advances and challenges in its theoretical foundation and technology basis, and the developments in its traditional and new emerging areas of applications. The diversity, novelty, and span of the work unfolding in these areas reveal the field's increased maturity and expanded scope and define the state of the art of robotics and its future direction.

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 Economic Model Predictive Control written by Matthew Ellis and published by Springer. This book was released on 2016-07-27 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes.In addition to being mathematically rigorous, these methods accommodate key practical issues, for example, direct optimization of process economics, time-varying economic cost functions and computational efficiency. Numerous comments and remarks providing fundamental understanding of the merging of process economics and feedback control into a single framework are included. A control engineer can easily tailor the many detailed examples of industrial relevance given within the text to a specific application. The authors present a rich collection of new research topics and references to significant recent work making Economic Model Predictive Control an important source of information and inspiration for academics and graduate students researching the area and for process engineers interested in applying its ideas.

Download or read book Geometric Model Predictive Control for Quadrotors with Bidirecional Thrust written by Jad Wehbeh and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Quadrotor vehicles have emerged as popular aerial platforms for a wide range of commercial endeavours, and have attracted significant attention from the research community. Augmenting quadrotor platforms with bidirectional actuators, which can reverse the direction of rotation of their propellers to invert the direction of thrust, has been suggested as a means of expanding the flight envelope of the vehicles. Exploiting this added functionality, however, noticeably complicates the control problem for the platforms, and necessitates special consideration of the motor dynamics.This thesis aims to examine the use of model predictive control (MPC) for quadrotors with bidirectional thrust capabilities through aerobatic flight, recovery from propeller loss, and operation under model and state uncertainty. The thesis starts by introducing the nonlinear dynamics for the vehicle and the bidirectional actuators, and derives a novel time-dependent affine approximation of the system dynamics using a linearization on the Lie algebra of SO(3). Then, building on this affine model, we obtain a new geometric MPC algorithm that does not require operating around equilibrium state-input pairs. A method for ensuring the controller satisfies the nonlinear motor constraints involved with bidirectional thrust is also suggested. Our proposed controller is evaluated in a simulation environment, where it outperforms an equivalent Euler-angle based approach on a range of aerobatic maneuvers.Moving beyond the fully-operational scenario, the thesis considers the problem of recovery from actuator failure through the use of MPC on reduced attitude representations, outlining two novel approaches suited to that purpose, and comparing them to established reduced-attitude controllers. Lastly, to address the issue of quadrotor control under state and parameter uncertainty, a scenario-based MPC variant is introduced alongside a more computationally tractable approximation of the same algorithm. The performance of these scenario-based formulations is tested through a series of Monte-Carlo simulations, where they are shown to result in improvements over the base MPC controller"--

Download or read book Model Based Control of Flying Robots for Robust Interaction Under Wind Influence written by Teodor Tomić and published by Springer Nature. This book was released on 2022-10-07 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the topic of autonomous flying robots physically interacting with the environment under the influence of wind. It aims to make aerial robots aware of the disturbance, interaction, and faults acting on them. This requires reasoning about the external wrench (force and torque) acting on the robot and distinguishing between wind, interactions, and collisions. The book takes a model-based approach and covers a systematic approach to parameter identification for flying robots. The book aims to provide a wind speed estimate independent of the external wrench, including estimating the wind speed using motor power measurements. Aerodynamics modeling is approached in a data-driven fashion, using ground-truth measurements from a 4D wind tunnel. Finally, the book bridges the gap between trajectory tracking and interaction control, to allow physical interaction under wind influence. Theoretical results are accompanied by extensive simulation and experimental results.