Download or read book Trajectory tracking path following and learning in model predictive control written by Fabian Russell Pfitz and published by Logos Verlag Berlin GmbH. This book was released on 2023-08-21 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we present novel model predictive control (MPC) formulations based on a convex open-loop optimal control problem to tackle the problem setup of trajectory tracking and path following as well as the control of systems with unknown system dynamic. In particular, we consider the framework of relaxed barrier function based MPC (rbMPC). We extend the existing stability theory to the trajectory tracking and the path following problem. We establish important system theoretic properties like closed-loop stability and exact constraint satisfaction under suitable assumptions. Moreover, we evaluate the developed MPC algorithms in the area of automated driving in simulations as well as in a real-world driving scenario. Further, we consider the control of completely unknown systems based on online optimization. We divide the overall problem into the design of an estimation algorithm and a control algorithm. The control algorithm is a model-independent receding horizon control algorithm in which important system theoretic properties like convergence to the origin are guaranteed without the knowledge of the true system parameters. The estimation and control algorithm are combined together and convergence to the origin of the closed-loop system for fully unknown linear time-invariant discrete-time systems is shown.

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 692 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 Reinforcement Learning for Optimal Feedback Control written by Rushikesh Kamalapurkar and published by Springer. This book was released on 2018-05-10 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements. This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.

Download or read book Field and Service Robotics written by Alonzo Kelly and published by Springer Science & Business Media. This book was released on 2010-06-28 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robotics is undergoing a major transformation in scope and dimension. From a largely dominant industrial focus, robotics is rapidly expanding into human en- ronments and vigorously engaged in its new challenges. Interacting with, assi- ing, serving, and exploring with humans, the emerging robots will increasingly touch people and their lives. Beyond its impact on physical robots, the body of knowledge robotics has p- duced is revealing a much wider range of applications reaching across diverse research areas and scientific disciplines, such as: biomechanics, haptics, neuros- ences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an abundant source of stimulation and insights for the field of robotics. It is indeed at the int- section of disciplines that the most striking advances happen. The Springer Tracts in Advanced Robotics (STAR) is devoted to bringing to the research community the latest advances in the robotics field on the basis of their significance and quality. Through a wide and timely dissemination of critical - search developments in robotics, our objective with this series is to promote more exchanges and collaborations among the researchers in the community and c- tribute to further advancements in this rapidly growing field.

Download or read book Predictive Control for Linear and Hybrid Systems written by Francesco Borrelli and published by Cambridge University Press. This book was released on 2017-06-22 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

Download or read book Cognitive Systems and Information Processing written by Fuchun Sun and published by Springer Nature. This book was released on 2023-12-06 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set CCIS 1918 and 1919 constitutes the refereed post-conference proceedings of the 8th International Conference on Cognitive Systems and Information Processing, ICCSIP 2023, held in Luoyang, China, during August 10–12, 2023. The 52 full papers presented in these proceedings were carefully reviewed and selected from 136 submissions. The papers are organized in the following topical sections: Volume I : Award; Algorithm & Control; and Application. Volume II: Robotics & Bioinformatics; and Vision.

Download or read book Advances in Mechanism Machine Science and Engineering in China written by Xinjun Liu and published by Springer Nature. This book was released on 2023-05-31 with total page 2228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the conference proceedings of the 23rd IFToMM China International Conference on Mechanism and Machine Science & Engineering (IFToMM CCMMS 2022). CCMMS was initiated in 1982, and it is the most important forum held in China for the exchange of research ideas, presentation of technical and scientific achievements, and discussion of future directions in the field of mechanism and machine science. The topics include parallel/hybrid mechanism synthesis and analysis, theoretical & computational kinematics, compliant mechanisms and micro/nano-mechanisms, reconfigurable and metamorphic mechanisms, space structures, mechanisms and materials, structure adaptation in space environment and ground testing, large-scale membrane deployable structures, construction and application of super-scale space systems, cams, gears and combining mechanisms, fluid power mechatronics drivetrain, mechanical design theory and methods, dynamics and vibration control, mechatronics, biologically inspired mechanisms and robotics, medical & rehabilitation robotics, mobile robotics, soft robotics, heavy non-road mobile machine, robot applications, engineering education on mechanisms, machines, and robotics. This book provides a state-of-the-art overview of current advances in mechanism and machine science in China. The inspiring ideas presented in the papers enlighten academic research and industrial application. The potential readers include academic researchers and industrial professionals in mechanism and machine science.

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 Proceedings of China SAE Congress 2023 Selected Papers written by China Society of Automotive Engineers and published by Springer Nature. This book was released on with total page 1601 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advances in Maritime Technology and Engineering written by Carlos Guedes Soares and published by CRC Press. This book was released on 2024-05-08 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Maritime Technology and Engineering comprises a collection of the papers presented at the 7th International Conference on Maritime Technology and Engineering (MARTECH 2024) held in Lisbon, Portugal, on 14-16 May 2024. This Conference has evolved from the series of biannual national conferences in Portugal, which have become an international event, reflecting the internationalization of the maritime sector and its activities. MARTECH 2024 is the seventh of this new series of biannual conferences. This book comprises 142 contributions that were reviewed by an International Scientific Committee. Advances in Maritime Technology and Engineering is dedicated to maritime transportation, ports as well as maritime safety and reliability. It further comprises sections dedicated to ship design, cruise ship design, and to the structural aspects of ship design, such as ultimate strength and composites, subsea structures as pipelines, and to ship building and ship repair. The Proceedings in Marine Technology and Ocean Engineering series is dedicated to the publication of proceedings of peer-reviewed international conferences dealing with various aspects of “Marine Technology and Ocean Engineering”. The series includes the proceedings of the following conferences: the International Maritime Association of the Mediterranean (IMAM) conferences, the Marine Structures (MARSTRUCT) conferences, the Renewable Energies Offshore (RENEW) conferences and the Maritime Technology (MARTECH) conferences. The “Marine Technology and Ocean Engineering” series is also open to new conferences that cover topics on the sustainable exploration of marine resources in various fields, such as maritime transport and ports, usage of the ocean including coastal areas, nautical activities, the exploration and exploitation of mineral resources, the protection of the marine environment and is resources, and risk analysis, safety and reliability. The aim of the series is to stimulate advanced education and training through the wide dissemination of the results of scientific research.

Download or read book Microelectronics Communication Systems Machine Learning and Internet of Things written by Vijay Nath and published by Springer Nature. This book was released on 2022-07-11 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents peer-reviewed papers of the First International Conference on Microelectronics, Communication Systems, Machine Learning, and the Internet of Things (MCMI-2020). This book discusses recent trends in technology and advancement in microelectronics, nano-electronics, VLSI design, IC technologies, wireless communications, optical communications, SoC, advanced instrumentations, signal processing, internet of things, machine learning, image processing, green energy, hybrid vehicles, weather forecasting, cloud computing, renewable energy, CMOS sensors, actuators, RFID, transducers, real-time embedded system, sensor network and applications, EDA design tools and techniques, fuzzy logic & artificial intelligence, high-performance computer architecture, AI-based robotics & applications, brain-computer interface, deep learning, advanced operating systems, supply chain development & monitoring, physical systems design, ICT applications, e-farming, information security, etc. It includes original papers based on theoretical, practical, experimental, simulations, development, application, measurement, and testing. The applications and solutions discussed in the book will serve as good reference material for young scholars, researchers, and academics.

Download or read book The Proceedings of the 18th Annual Conference of China Electrotechnical Society written by Qingxin Yang and published by Springer Nature. This book was released on with total page 930 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 Passivity Based Model Predictive Control for Mobile Vehicle Motion Planning written by Adnan Tahirovic and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehicle navigation in both indoor and outdoor environments. The brief also introduces analysis of the worst-case scenario that might occur during the task execution. Some of the questions answered in the text include: • how to use an MPC optimization framework for the mobile vehicle navigation approach; • how to guarantee safe task completion even in complex environments including obstacle avoidance and sideslip and rollover avoidance; and • what to expect in the worst-case scenario in which the roughness of the terrain leads the algorithm to generate the longest possible path to the goal. The passivity-based MPC approach provides a framework in which a wide range of complex vehicles can be accommodated to obtain a safer and more realizable tool during the path-planning stage. During task execution, the optimization step is continuously repeated to take into account new local sensor measurements. These ongoing changes make the path generated rather robust in comparison with techniques that fix the entire path prior to task execution. In addition to researchers working in MPC, engineers interested in vehicle path planning for a number of purposes: rescued mission in hazardous environments; humanitarian demining; agriculture; and even planetary exploration, will find this SpringerBrief to be instructive and helpful.

Download or read book Cognitive Informatics Computer Modelling and Cognitive Science written by G. R. Sinha and published by Academic Press. This book was released on 2020-04-22 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Informatics, Computer Modelling, and Cognitive Science: Theory, Case Studies, and Applications presents the theoretical background and history of cognitive science to help readers understand its foundations, philosophical and psychological aspects, and applications in a wide range of engineering and computer science case studies. Cognitive science, a cognitive model of the brain, knowledge representation, and information processing in the human brain are discussed, as is the theory of consciousness, neuroscience, intelligence, decision-making, mind and behavior analysis, and the various ways cognitive computing is used for information manipulation, processing and decision-making. Mathematical and computational models, structures and processes of the human brain are also covered, along with advances in machine learning, artificial intelligence, cognitive knowledge base, deep learning, cognitive image processing and suitable data analytics. Identifies how foundational theories and concepts in cognitive science are applicable in other fields Includes a comprehensive review of cognitive science applications in multiple domains, applying it to neural engineering, robotics, computer science and STEM Includes models of brain processing, consciousness, decision-making, and more Provides in-depth technical coverage of cognitive informatics and computing, including coverage of cognitive knowledge base, information theory, cognitive machine learning and intelligence

Download or read book Trajectory Tracking with Fault tolerant Flight Control System written by Fabio Andrade de Almeida and published by . This book was released on 2009 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Decision Making Planning and Control Strategies for Intelligent Vehicles written by Haotian Cao and published by Springer Nature. This book was released on 2022-05-31 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The intelligent vehicle will play a crucial and essential role in the development of the future intelligent transportation system, which is developing toward the connected driving environment, ultimate driving safety, and comforts, as well as green efficiency. While the decision making, planning, and control are extremely vital components of the intelligent vehicle, these modules act as a bridge, connecting the subsystem of the environmental perception and the bottom-level control execution of the vehicle as well. This short book covers various strategies of designing the decision making, trajectory planning, and tracking control, as well as share driving, of the human-automation to adapt to different levels of the automated driving system. More specifically, we introduce an end-to-end decision-making module based on the deep Q-learning, and improved path-planning methods based on artificial potentials and elastic bands which are designed for obstacle avoidance. Then, the optimal method based on the convex optimization and the natural cubic spline is presented. As for the speed planning, planning methods based on the multi-object optimization and high-order polynomials, and a method with convex optimization and natural cubic splines, are proposed for the non-vehicle-following scenario (e.g., free driving, lane change, obstacle avoidance), while the planning method based on vehicle-following kinematics and the model predictive control (MPC) is adopted for the car-following scenario. We introduce two robust tracking methods for the trajectory following. The first one, based on nonlinear vehicle longitudinal or path-preview dynamic systems, utilizes the adaptive sliding mode control (SMC) law which can compensate for uncertainties to follow the speed or path profiles. The second one is based on the five-degrees-of-freedom nonlinear vehicle dynamical system that utilizes the linearized time-varying MPC to track the speed and path profile simultaneously. Toward human-automation cooperative driving systems, we introduce two control strategies to address the control authority and conflict management problems between the human driver and the automated driving systems. Driving safety field and game theory are utilized to propose a game-based strategy, which is used to deal with path conflicts during obstacle avoidance. Driver's driving intention, situation assessment, and performance index are employed for the development of the fuzzy-based strategy. Multiple case studies and demos are included in each chapter to show the effectiveness of the proposed approach. We sincerely hope the contents of this short book provide certain theoretical guidance and technical supports for the development of intelligent vehicle technology.