Download or read book Adaptive and Learning Controllers for High Accuracy Trajectory Tracking in Changing Conditions written by Karime Pereida and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robots are expected to perform tasks reliably in unknown and dynamic environments, which can include unknown disturbances and changing dynamics. This thesis investigates controllers for high-accuracy trajectory tracking of quadrotors in changing conditions. The proposed controllers use $\mathcal{L}_1$ adaptive control to handle disturbances and learning- and optimization-based controllers to improve tracking in changing conditions. The underlying $\Lone$ adaptive controller forces systems subject to unknown disturbances and changing dynamics to behave close to a specified reference model. Learning- and optimization-based controllers improve the tracking performance of the $\mathcal{L}_1$ controlled systems. This thesis presents five frameworks: \begin{enumerate*} \item Iterative Learning Control (ILC), \item Multi-Robot Transfer Learning, \item Multi-Robot, Multi-Task Transfer Learning, \item Adaptive Model Predictive Control (MPC), and \item Robust, Adaptive Model Predictive Control. \end{enumerate*} ILC calculates a feedforward input that minimizes tracking error by using information from previous iterations of the same trajectory. ILC assumes the system has a repeatable behaviour, which may not be true in changing conditions. Repeatability is achieved by using an underlying $\mathcal{L}_1$ adaptive controller. Dynamically different systems can behave in the same specified way if they are equipped with an $\mathcal{L}_1$ adaptive controller. Hence, trajectories learned on one system can directly be transferred to a dynamically different system in a Multi-Robot Transfer Learning framework. Typically, a new learning process has to be started for each desired trajectory. The Multi-Task Transfer Learning framework uses insights from control systems theory to generalize previously learned tasks and enable a Multi-Robot, Multi-Task Transfer Learning framework. In order to eliminate the need for a learning phase to achieve high-accuracy trajectory tracking, $\mathcal{L}_1$ adaptive control is combined with model predictive control. The proposed adaptive MPC leverages the performance guarantees of $\mathcal{L}_1$ adaptive controller to improve tracking performance on the first iteration. However, modelling errors may remain despite the presence of the $\mathcal{L}_1$ adaptive controller. Therefore, we propose and show performance guarantees of a robust adaptive MPC that is robust to modelling errors and improves the trajectory tracking performance in changing conditions. The proposed frameworks were implemented on the Parrot AR.Drone 2.0 and Bebop 2 quadrotors and showed high-accuracy trajectory tracking in changing conditions.
Download or read book AI based Robot Safe Learning and Control written by Xuefeng Zhou and published by Springer. This book was released on 2020-09-18 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.
Download or read book Adaptive and Iterative Learning Control for Robot Trajectory Tracking written by YU-HSIU LEE and published by . This book was released on 2019 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis develops adaptive and iterative learning control methods for robot trajectory tracking applications. Specifically, iterative learning control is applied when a desired reference trajectory is known beforehand, and adaptive control is designed to cope with unknown patient motion (disturbance) in MRI-guided robot-assisted intervention. For robot manipulator tracking, a nested-loop iterative learning control is proposed. This method requires only nominal kinematic parameters from factory setting, gives fast convergence, and can be added on top of existing servo loop. The ILC learning architecture includes an inner loop that accounts for motor dynamics, and an outer loop that addresses the static bias from the payload or imprecise kinematics. A data-based learning filter design is extended to cope with motion constraint and multivariate systems. It is experimentally verified on a 6-DOF serial robot that the proposed method mitigates the maximum dynamic tracking error by an order of magnitude, and is applicable to different payloads due to small system variation from torque shielding of gear reduction. For tracking of general nonlinear dynamic systems, an efficient data-driven ILC algorithm is proposed. As opposed to the model-based methods, for which nonlinear identification and learning law design can be cumbersome, this method uses adaptive filter to implicitly (and automatically) construct linearized system inverse for effective learning. An existing adjoint-based ILC for LTI system is also extended to cope with nonlinear dynamics, and for comparative study. The SISO algorithms are simulated and experimentally validated on a fully-actuated 2-DOF laboratory pendulum system. Algorithms are also developed to circumvent the difficulty when adapting a right inverse for MIMO systems. The automated MRI-guided intervention is motivated by the current procedural inefficiency from constraints posed by MR environment. As lots of researchers focus on either MR-safe/conditional robot to augment the reach of the physician, or MR image tracking for motion estimation of tissue/instrument, this work aims at addressing a more flexible setting: use real-time MRI for instrument control when a target is in motion. It is enabled via the integration of robot hardware, MRI sensing, and control techniques. On the control aspect, we characterize the MR imaging process and the robot dynamics, then propose adaptive control schemes to overcome the long delay and high noise variance from MRI measurement. The study is conducted on a hydrostatically actuated platform, which consists of a target motion module that emulates respiratory motion, and an instrument manipulation module regulating the instrument-target distance.
Download or read book Learning for Adaptive and Reactive Robot Control written by Aude Billard and published by MIT Press. This book was released on 2022-02-08 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Download or read book A Fast Trajectory Tracking Adaptive Controller for Robot Manipulators written by Shinsuke Tagami and published by . This book was released on 1993 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: An adaptive decentralized nonlinear controller for a robot manipulator is presented in this thesis. Based on the adaptive control schemes designed by Seraji [18], Dai [30], and Jimenez [31], we redesigned and further simplified the control algorithm and, as a consequence, we achieved better path tracking performance. The proposed adaptive controller is made of a PD feedback controller which has time varying gains, a feedforward compensator based on the idea of inverse dynamics, and an auxiliary signal. Due to its adaptive structure, the controller shows robustness against disturbances and unmodeled dynamics. In order to ensure asymptotic tracking we select a Lyapunov function such that the controller forces the negative definiteness of the time derivative of such a Lyapunov function. To do this, the tracking position and velocity error are penalized and used as a part of the adaptive control gain. The main advantages of this scheme are the comparably faster convergence of tracking error, relatively simpler structure, and smoother control activity. This controller only requires the position and angular speed measurement, it does not require any knowledge about the mathematical model of the robot manipulator. Simulation shows the capacity of this controller and its robustness against disturbances.
Download or read book Advances in Robots Trajectories Learning via Fast Neural Networks written by Jose De Jesus Rubio and published by Frontiers Media SA. This book was released on 2021-05-14 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Direct Adaptive Control for a Trajectory Tracking UAV written by Nirmit Prabhakar and published by . This book was released on 2018 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research focuses on the theoretical development and analysis of a direct adaptive control algorithm to enable fixed-wing UAV to track reference trajectories while in the presence of persistent external disturbances. A typical application of this work is autonomous flight though urban environments, where reference trajectories would be provided by a path planning algorithm and the vehicle would be subjected to significant wind gust disturbances. Full 6-DOF nonlinear and linear UAV simulation models are developed and used to study the performance of the direct adaptive control system for various scenarios. A stability proof is developed to prove convergence of the direct adaptive control system under certain conditions. Specific adaptive controller implementation details are provided, including the use of a sensor blending algorithm to address the non-minimum phase properties of the UAV models. The robustness of the adaptive system pertaining to the amount of modeling error that can be accommodated by the controller is studied, and the disturbance rejection capabilities and limitations of the controllers are also analyzed. The overall results of this research demonstrate that the direct adaptive control algorithm can enable trajectory tracking in cases where there are both significant uncertainties in the external disturbances and considerable error in the UAV model.
Download or read book Modeling and Control of Batch Processes written by Prashant Mhaskar and published by Springer. This book was released on 2018-11-28 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and Control of Batch Processes presents state-of-the-art techniques ranging from mechanistic to data-driven models. These methods are specifically tailored to handle issues pertinent to batch processes, such as nonlinear dynamics and lack of online quality measurements. In particular, the book proposes: a novel batch control design with well characterized feasibility properties; a modeling approach that unites multi-model and partial least squares techniques; a generalization of the subspace identification approach for batch processes; and applications to several detailed case studies, ranging from a complex simulation test bed to industrial data. The book’s proposed methodology employs statistical tools, such as partial least squares and subspace identification, and couples them with notions from state-space-based models to provide solutions to the quality control problem for batch processes. Practical implementation issues are discussed to help readers understand the application of the methods in greater depth. The book includes numerous comments and remarks providing insight and fundamental understanding into the modeling and control of batch processes. Modeling and Control of Batch Processes includes many detailed examples of industrial relevance that can be tailored by process control engineers or researchers to a specific application. The book is also of interest to graduate students studying control systems, as it contains new research topics and references to significant recent work. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Download or read book Adaptive Control for Robotic Manipulators written by Dan Zhang and published by CRC Press. This book was released on 2017-02-03 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: The robotic mechanism and its controller make a complete system. As the robotic mechanism is reconfigured, the control system has to be adapted accordingly. The need for the reconfiguration usually arises from the changing functional requirements. This book will focus on the adaptive control of robotic manipulators to address the changed conditions. The aim of the book is to summarise and introduce the state-of-the-art technologies in the field of adaptive control of robotic manipulators in order to improve the methodologies on the adaptive control of robotic manipulators. Advances made in the past decades are described in the book, including adaptive control theories and design, and application of adaptive control to robotic manipulators.
Download or read book Advances in Guidance Navigation and Control written by Liang Yan and published by Springer Nature. This book was released on 2023-02-10 with total page 7455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircrafts. It covers a wide range of topics, including but not limited to, intelligent computing communication and control; new methods of navigation, estimation and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation and control of miniature aircraft; and sensor systems for guidance, navigation and control etc. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.
Download or read book Applied Mechatronics and Android Robotics written by Ching Kuo Wang and published by Trans Tech Publications Ltd. This book was released on 2013-09-03 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collection of selected, peer reviewed papers from the International Conference on Applied Mechatronics and Android Robotics (ICAMAR 2013), July 13-14, Taipei, Taiwan. Volume is indexed by Thomson Reuters CPCI-S (WoS). The 56 papers are grouped as follows: Chapter 1: Robot Design, Motion Planning and Robot Control; Chapter 2: System of Automation, Control and Measurement; Chapter 3: Manufacturing and Industry Engineering; Chapter 4: Information System, Data Processing and Network Application.
Download or read book Cardiovascular engineering written by Christopher T. Nguyen and published by Frontiers Media SA. This book was released on 2022-12-16 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Unmanned Aerial Systems written by Anis Koubaa and published by Academic Press. This book was released on 2021-01-21 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Systems: Theoretical Foundation and Applications presents some of the latest innovative approaches to drones from the point-of-view of dynamic modeling, system analysis, optimization, control, communications, 3D-mapping, search and rescue, surveillance, farmland and construction monitoring, and more. With the emergence of low-cost UAS, a vast array of research works in academia and products in the industrial sectors have evolved. The book covers the safe operation of UAS, including, but not limited to, fundamental design, mission and path planning, control theory, computer vision, artificial intelligence, applications requirements, and more. This book provides a unique reference of the state-of-the-art research and development of unmanned aerial systems, making it an essential resource for researchers, instructors and practitioners. Covers some of the most innovative approaches to drones Provides the latest state-of-the-art research and development surrounding unmanned aerial systems Presents a comprehensive reference on unmanned aerial systems, with a focus on cutting-edge technologies and recent research trends in the area
Download or read book 2021 IEEE 4th Advanced Information Management Communicates Electronic and Automation Control Conference IMCEC written by IEEE Staff and published by . This book was released on 2021-06-18 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of IMCEC 2021 is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in Advanced Information Management,Communicates,Electronic and Automation Control It provides opportunities for the delegates to exchange new ideas and application experiences, to establish business or research relations and to find global partners for future collaboration
Download or read book Improved Lyapunov based Decentralized Adaptive Controller written by Reza A. Dai and published by . This book was released on 1991 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: An improved robot manipulator decentralized non-linear adaptive controller that performs well in the presence of disturbances with unknown parameters and non-linearities is presented in this work. The proposed decentralized adaptive structure is a modification of the controller developed by Seraji [13-17] and is characterized by an auxiliary signal that compensates for the unmodeled dynamics and improves the tracking performance, by a feedforward component based on the inverse system to ensure high performance over a wide range and by a PD feedback component of constant gain to improve the speed of response of the system. As a result, a very accurate and fast path tracking is achieved despite the non-linearities. The scheme requires only the measurement of angular speed and displacement of each joint, and it does not require any knowledge about the mathematical model of the manipulator. Due to its decentralized structure, it can be implemented on parallel processors to speed up the operation. The main advantages of the proposed control scheme over similar controllers are that the control activity is smoother, it is less sensitive to sampling size and to the time period elapsed when the whole trajectory is traversed, as verified by simulations of several test conditions of-two of the joints of the PUMA 560 robot arm.
Download or read book Adaptive Tracking Control of On Line Path Planners Velocity Fields and Navigation Functions written by and published by . This book was released on 2004 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditionally, robot control research has focused on the position tracking problem where the objective is to force the robot's end-effector to follow an a priori known desired time dependent trajectory. Motivated by task objectives that are more effectively described by on-line, state-dependent trajectories, two adaptive tracking controllers are developed in this paper that accommodate on-line path planning objective. An example adaptive controller is first modified to achieve velocity field tracking in the presence of parametric uncertainty in the robot dynamics. The development aims to relax the typical assumption that the integral of the velocity field is bounded by incorporating a norm- squared gradient term in the control design so that the boundedness of all signals can be proven. An extension is then provided that targets the trajectory planning problem where the task objective can be described as the desire to move to a goal configuration while avoiding known obstacles. Specifically, an adaptive navigation function based controller is designed to provide a path from an initial condition inside the free configuration space of the robot manipulator to the goal configuration. Experimental results for each controller are provided to illustrate proof of validation of the approaches.
