Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences

Game-Theoretic Safety Assurance for Human-Centered Robotic Systems

In order for autonomous systems like robots, drones, and self-driving cars to be reliably introduced into our society, they must have the ability to actively account for safety during their operation. While safety analysis has traditionally been conducted offline for controlled environments like cages on factory floors, the much higher complexity of open, human-populated spaces like our homes, cities, and roads makes it unviable to rely on common design-time assumptions, since these may be violated once the system is deployed. Instead, the next generation of robotic technologies will need to reason about safety online, constructing high-confidence assurances informed by ongoing observations of the environment and other agents, in spite of models of them being necessarily fallible.This dissertation aims to lay down the necessary foundations to enable autonomous systems to ensure their own safety in complex, changing, and uncertain environments, by explicitly reasoning about the gap between their models and the real world. It first introduces a suite of novel robust optimal control formulations and algorithmic tools that permit tractable safety analysis in time-varying, multi-agent systems, as well as safe real-time robotic navigation in partially unknown environments; these approaches are demonstrated on large-scale unmanned air traffic simulation and physical quadrotor platforms. After this, it draws on Bayesian machine learning methods to translate model-based guarantees into high-confidence assurances, monitoring the reliability of predictive models in light of changing evidence about the physical system and surrounding agents. This principle is first applied to a general safety framework allowing the use of learning-based control (e.g. reinforcement learning) for safety-critical robotic systems such as drones, and then combined with insights from cognitive science and dynamic game theory to enable safe human-centered navigation and interaction; these techniques are showcased on physical quadrotors—flying in unmodeled wind and among human pedestrians—and simulated highway driving. The dissertation ends with a discussion of challenges and opportunities ahead, including the bridging of safety analysis and reinforcement learning and the need to ``close the loop'' around learning and adaptation in order to deploy increasingly advanced autonomous systems with confidence

New Approaches in Automation and Robotics

The book New Approaches in Automation and Robotics offers in 22 chapters a collection of recent developments in automation, robotics as well as control theory. It is dedicated to researchers in science and industry, students, and practicing engineers, who wish to update and enhance their knowledge on modern methods and innovative applications. The authors and editor of this book wish to motivate people, especially under-graduate students, to get involved with the interesting field of robotics and mechatronics. We hope that the ideas and concepts presented in this book are useful for your own work and could contribute to problem solving in similar applications as well. It is clear, however, that the wide area of automation and robotics can only be highlighted at several spots but not completely covered by a single book

Intelligent and High-Performance Behavior Design of Autonomous Systems via Learning, Optimization and Control

Nowadays, great societal demands have rapidly boosted the development of autonomous systems that densely interact with humans in many application domains, from manufacturing to transportation and from workplaces to daily lives. The shift from isolated working environments to human-dominated space requires autonomous systems to be empowered to handle not only environmental uncertainties such as external vibrations but also interaction uncertainties arising from human behavior which is in nature probabilistic, causal but not strictly rational, internally hierarchical and socially compliant.This dissertation is concerned with the design of intelligent and high-performance behavior of such autonomous systems, leveraging the strength from control, optimization, learning, and cognitive science. The work consists of two parts. In Part I, the problem of high-level hybrid human-machine behavior design is addressed. The goal is to achieve safe, efficient and human-like interaction with people. A framework based on the theory of mind, utility theories and imitation learning is proposed to efficiently represent and learn the complicated behavior of humans. Built upon that, machine behaviors at three different levels - the perceptual level, the reasoning level, and the action level - are designed via imitation learning, optimization, and online adaptation, allowing the system to interpret, reason and behave as human, particularly when a variety of uncertainties exist. Applications to autonomous driving are considered throughout Part I. Part II is concerned with the design of high-performance low-level individual machine behavior in the presence of model uncertainties and external disturbances. Advanced control laws based on adaptation, iterative learning and the internal structures of uncertainties/disturbances are developed to assure that the high-level interactive behaviors can be reliably executed. Applications on robot manipulators and high-precision motion systems are discussed in this part

State relativity and speed-allocated line-of-sight course control for path-following of underwater vehicles

Path-following is a primary task for most marine, air or space crafts, especially during autonomous operations. Research on autonomous underwater vehicles (AUV) has received large interests in the last few decades with research incentives emerging from the safe, cost-effective and practical solutions provided by their applications such as search and rescue, inspection and monitoring of pipe-lines ans sub-sea structures. This thesis presents a novel guidance system based on the popular line-of-sight (LOS) guidance law for path-following (PF) of underwater vehicles (UVs) subject to environmental disturbances. Mathematical modeling and dynamics of (UVs) is presented first. This is followed by a comprehensive literature review on guidance-based path-following control of marine vehicles, which includes revised definitions of the track-errors and more detailed illustrations of the general PF problem. A number of advances on relative equations of motion are made, which include an improved understanding of the fluid FLOW frame and expression of its motion states, an analytic method of modeling the signs of forces and moments and the proofs of passivity and boundedness of relative UV systems in 3-D. The revision in the relative equations of motion include the concept of state relativity, which is an improved understanding of relativity of motion states expressed in reference frames and is also useful in incorporating environmental disturbances. In addition, the concept of drift rate is introduced along with a revision on the angles of motion in 3-D. A switching mechanism was developed to overcome a drawback of a LOS guidance law, and the linear and nonlinear stability results of the LOS guidance laws have been provided, where distinctions are made between straight and curved PF cases. The guidance system employs the unique formulation and solution of the speed allocation problem of allocating a desired speed vector into x and y components, and the course control that employs the slip angle for desired heading for disturbance rejection. The guidance system and particularly the general course control problem has been extended to 3-D with the new definition of vertical-slip angle. The overall guidance system employing the revised relative system model, course control and speed allocation has performed well during path-following under strong ocean current and/or wave disturbances and measurement noises in both 2-D and 3-D scenarios. In 2-D and 3-D 4 degrees-of-freedom models (DOF), the common sway-underactuated and fully actuated cases are considered, and in 3-D 5-DOF model, sway and heave underactuated and fully actuated cases are considered. Stability results of the LOS guidance laws include the semi-global exponential stability (SGES) of the switching LOS guidance and enclosure-based LOS guidance for straight and curved paths, and SGES of the loolahead-based LOS guidance laws for curved paths. Feedback sliding mode and PID controllers are applied during PF providing a comparison between them, and simulations are carried out in MatLab

Nonlinear Controller Design for UAVs with Time-Varying Aerodynamic Uncertainties

Unmanned Aerial Vehicles (UAVs) are here and they are here to stay. Unmanned Aviation has expanded significantly in recent years and research and development in the field of navigation and control have advanced beyond expectations. UAVs are currently being used for defense programs around the world but the range of applications is expected to grow in the near future, with civilian applications such as environmental and aerial monitoring, aerial surveillance and homeland security being some representative examples. Conventional and commercially available small-scale UAVs have limited utilization and applicability to executing specific short-duration missions because of limitations in size, payload, power supply and endurance. This fact has already marked the dawn of a new era of more powerful and versatile UAVs (e.g. morphing aircraft), able to perform a variety of missions. This dissertation presents a novel, comprehensive, step-by-step, nonlinear controller design framework for new generation, non-conventional UAVs with time-varying aerodynamic characteristics during flight. Controller design for such UAVs is a challenging task mainly due to uncertain aerodynamic parameters in the UAV mathematical model. This challenge is tackled by using and implementing μ-analysis and additive uncertainty weighting functions. The technique described herein can be generalized and applied to the class of non-conventional UAVs, seeking to address uncertainty challenges regarding the aircraft\u27s aerodynamic coefficients

Robust Operation and Control Synthesis of Autonomous Mobile Rack Vehicle in the Smart Warehouse

Nowadays, with the development of science and technology, to manage the inventory in the warehouse more efficiency, so the warehouse must have the stability and good operation chain such as receive and transfer the product to customer, storage the inventory, manage the location, making the barcode...in that operation chain, storage the inventory in the warehouse is most important thing that we must consider. In addition, to reduce costs for larger warehouse or expand the floor space of the small warehouse, it is impossible to implement this with a traditional warehouse. The warehouse is called the traditional warehouse when it uses the fixed rack. To build this type of warehouse, the space for storage must be very large. However, the cost for renting or buying the large warehouse is too expensive, so to reduce cost and build the flexible warehouse which can store the huge quantity of product within limited area, then the smart warehouse is necessary to consider. The smart warehouse system with autonomous mobile rack vehicles (MRV) increases the space utilization by providing only a few open aisles at a time for accessing the racks with minimal intervention. It is always necessary to take into account the mobile-rack vehicles (or autonomous logistics vehicles). This thesis deals with designing the robust controller for maintaining safe spacing with collision avoidance and lateral movement synchronization in the fully automated warehouse. The compact MRV dynamics are presented for the interconnected string of MRV with communication delay. Next, the string stability with safe working space of the MRV has been described for guaranteeing complete autonomous logistics in the extremely cold environment without rail rack. In addition, the controller order has been significantly reduced to the low-order system without serious performance degradation. Finally, this control method addresses the control robustness as well as the performances of MRV against unavoidable uncertainties, disturbances, and noises for warehouse automation.Contents List of Tables vii List of Figures viii Chapter 1. Introduction 1 1.1 Mobile rack vehicle 2 1.2 Leader and following vehicle 5 1.2.1 Cruise control 5 1.2.2 Adaptive cruise control 6 1.2.3 String stability of longitudinal vehicle platoon 10 1.2.4 String stability of lateral vehicle platoon 15 1.3 Problem definition 20 1.4 Purpose and aim 21 1.5 Contribution 22 Chapter 2. Robust control synthesis 23 2.1 Introduction 23 2.2 Uncertainty modeling 23 2.2.1 Unstructured uncertainties 24 2.2.2 Parametric uncertainties 25 2.2.3 Structured uncertainties 26 2.2.4 Linear fractional transformation 26 2.2.5 Coprime factor uncertainty 27 2.3 Stability criterion 31 2.3.1 Small gain theorem 31 2.3.2 Structured singular value synthesis brief definition 33 2.4 Robustness analysis and controller design 34 2.4.1 Forming generalized plant and structure 34 2.4.2 Robustness analysis 37 2.5 Robust controller using loop shaping design 39 2.5.1 Stability robustness for a coprime factor plant description 41 2.6 Reduced controller 44 2.6.1 Truncation 45 2.6.2 Residualization 46 2.6.3 Balanced realization 47 2.6.4 Optimal Hankel norm approximation 48 Chapter 3. Dynamical model of mobile rack vehicle. 53 3.1 Dynamical model of longitudinal mobile rack vehicle 53 3.2 Dynamical model of lateral mobile rack vehicle 56 3.1.1 Kinematics and dynamics of mobile rack vehicles 56 3.1.2 Lateral vehicle model with nominal value 62 Chapter 4. Controller design for mobile rack vehicle 65 4.1 Robust controller synthesis for longitudinal of mobile rack vehicles 65 4.2 Robust controller synthesis for lateral of mobile rack vehicles 73 4.2.1 Lateral vehicle model with uncertainty description 74 4.2.2 Controller design 78 4.2.3 Robust performance problem 82 4.3 String stability of connected mobile rack vehicle 85 4.4 Lower order control synthesis 87 Chapter 5. Numerical simulation and discussion 92 5.1 Mobile rack longitudinal control simulation and discussion 92 5.2 Mobile rack lateral control simulation and discussion 99 Chapter 6. Conclusion 110 Reference 112Docto