Bounded Coordination Control of Second-order Dynamic Agents

This paper presents a constructive design of distributed and bounded coordination controllers that force mobile agents with second-order dynamics to track desired trajectories and to avoid collision between them. The control design is based on the new bounded control design technique for second-order systems, and new pairwise collision avoidance functions. The pair wise collision functions are functions of both the relative position and velocity of the agents instead of only the relative position as in the literature. Desired features of the proposed control design include:1) Boundedness of the control inputs by a predefined bound despite collision avoidance between the agentsconsidered,2) No collision between any agents,3) Asymptotical stability of desired equilibrium set, and4) Instability of all other undesired critical sets of the closed loop system. The proposed control design is then applied to design a coordination control system for a group of vertical take-off and landing (VTOL) aircraft

Outdoor operations of multiple quadrotors in windy environment

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV system, each sUAV has to locally counter the wind disturbance while maintaining the safety of the system. Such continuous manipulation of the control effort for multiple sUAVs under uncertain environmental conditions is computationally taxing and can lead to reduced efficiency and safety concerns. Additionally, modern day sUAV systems are susceptible to cyberattacks due to their use of commercial wireless communication infrastructure. This dissertation aims to address these multi-faceted challenges related to the operation of outdoor rotor-based multi-sUAV systems. A comprehensive review of four representative techniques to measure and estimate wind speed and direction using rotor-based sUAVs is discussed. After developing a clear understanding of the role wind gusts play in quadrotor motion, two decentralized motion planners for a multi-quadrotor system are implemented and experimentally evaluated in the presence of wind disturbances. The first planner is rooted in the reinforcement learning (RL) technique of state-action-reward-state-action (SARSA) to provide generalized path plans in the presence of wind disturbances. While this planner provides feasible trajectories for the quadrotors, it does not provide guarantees of collision avoidance. The second planner implements a receding horizon (RH) mixed-integer nonlinear programming (MINLP) model that is integrated with control barrier functions (CBFs) to guarantee collision-free transit of the multiple quadrotors in the presence of wind disturbances. Finally, a novel communication protocol using Ethereum blockchain-based smart contracts is presented to address the challenge of secure wireless communication. The U.S. sUAV market is expected to be worth $92 Billion by 2030. The Association for Unmanned Vehicle Systems International (AUVSI) noted in its seminal economic report that UAVs would be responsible for creating 100,000 jobs by 2025 in the U.S. The rapid proliferation of drone technology in various applications has led to an increasing need for professionals skilled in sUAV piloting, designing, fabricating, repairing, and programming. Engineering educators have recognized this demand for certified sUAV professionals. This dissertation aims to address this growing sUAV-market need by evaluating two active learning-based instructional approaches designed for undergraduate sUAV education. The two approaches leverages the interactive-constructive-active-passive (ICAP) framework of engagement and explores the use of Competition based Learning (CBL) and Project based Learning (PBL). The CBL approach is implemented through a drone building and piloting competition that featured 97 students from undergraduate and graduate programs at NJIT. The competition focused on 1) drone assembly, testing, and validation using commercial off-the-shelf (COTS) parts, 2) simulation of drone flight missions, and 3) manual and semi-autonomous drone piloting were implemented. The effective student learning experience from this competition served as the basis of a new undergraduate course on drone science fundamentals at NJIT. This undergraduate course focused on the three foundational pillars of drone careers: 1) drone programming using Python, 2) designing and fabricating drones using Computer-Aided Design (CAD) and rapid prototyping, and 3) the US Federal Aviation Administration (FAA) Part 107 Commercial small Unmanned Aerial Vehicles (sUAVs) pilot test. Multiple assessment methods are applied to examine the students’ gains in sUAV skills and knowledge and student attitudes towards an active learning-based approach for sUAV education. The use of active learning techniques to address these challenges lead to meaningful student engagement and positive gains in the learning outcomes as indicated by quantitative and qualitative assessments

Formation Control of Multiple Agents with Preserving Connectivity and its Application to Gradient Climbing

A design of cooperative controllers that force a group of N mobile agents with limited communication ranges to perform a desired formation is presented. The proposed formation control system also preserves initial communication connectivity and guarantees no collisions between the agents. The formation control design is based on smooth step functions, potential functions, and the Lyapunov direct method. The proposed formation control system is applied to solve a gradient climbing problem where the gradient average of a distributed field is estimated over a bounded region using the field measurement by the agents

Cooperative Control of Nonlinear Multi-Agent Systems

Multi-agent systems have attracted great interest due to their potential applications in a variety of areas. In this dissertation, a nonlinear consensus algorithm is developed for networked Euler-Lagrange multi-agent systems. The proposed consensus algorithm guarantees that all agents can reach a common state in the workspace. Meanwhile, the external disturbances and structural uncertainties are fundamentally considered in the controller design. The robustness of the proposed consensus algorithm is then demonstrated in the stability analysis. Furthermore, experiments are conducted to validate the effectiveness of the proposed consensus algorithm. Next, a distributed leader-follower formation tracking controller is developed for networked nonlinear multi-agent systems. The dynamics of each agent are modeled by Euler-Lagrange equations, and all agents are guaranteed to track a desired time-varying trajectory in the presence of noise. The fault diagnosis strategy of the nonlinear multi-agent system is also investigated with the help of differential geometry tools. The effectiveness of the proposed controller is verified through simulations. To further extend the application area of the multi-agent technique, a distributed robust controller is then developed for networked Lipschitz nonlinear multi-agent systems. With the appearance of system uncertainties and external disturbances, a sampled-data feedback control protocol is carried out through the Lyapunov functional approach. The effectiveness of the proposed controller is verified by numerical simulations. Other than the robustness and sampled-data information exchange, this dissertation is also concerned with the event-triggered consensus problem for the Lipschitz nonlinear multi-agent systems. Furthermore, the sufficient condition for the stochastic stabilization of the networked control system is proposed based on the Lyapunov functional method. Finally, simulation is conducted to demonstrate the effectiveness of the proposed control algorithm. In this dissertation, the cooperative control of networked Euler-Lagrange systems and networked Lipschitz systems is investigated essentially with the assistance of nonlinear control theory and diverse controller design techniques. The main objective of this work is to propose realizable control algorithms for nonlinear multi-agent systems

Multi-Agent Control for Pursuer Coordination in Reach Avoid Games

This work addresses the fast-evader problem in pursuit-evasion games, where multi-pursuer coordination is leveraged to successfully trade-off kinematic superiority with numbers. The design of pursuer team strategies is developed under the framework of multi-agent control (also referred to as swarm control). The objective is the design of local level rules for a team of pursuers that results in the desired global behavior (evader capture). To that end, this work addresses three main issues regarding the design of scalable solutions for pursuer coordination against a fast evader: trading-off kinematic superiority with numbers through coordination, selecting the sufficient number of pursuers to guarantee capture, decentralized approach to satisfying a team objective while enforcing constraints. Through the construction of a surrogate objective for evader capture, the problem of pur- suer coordination is converted to a coverage control problem. The coverage problem treats the pursuer capture sets as resources to be distributed over a domain, which successfully enables the synthesis of swarm control solutions. Pursuer team size selection is achieved by decomposing the coverage problem into a static formation requirement and a tracking performance requirement for the individual agents. Lastly, a decentralized formulation of the coordinated capture problem and a framework for the enforcement of agent interaction constraints in aggressively maneuvering environments are introduced

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance

Integrating geological uncertainty and dynamic data into modelling procedures for fractured reservoirs

Modelling, simulating and characterising flow through naturally fractured reservoirs is a multi-disciplinary effort. The scarcity of data combined with the additional layer of complexity that fractures add to a reservoir makes an efficient integration of all available data fundamental. However, the vast range of data types to be considered and the multitude of disciplines giving their input often results in communication barriers and individuals working within their comfort area, creating further challenges for uncertainty propagation. It is however critical for decision-making to develop geologically consistent reservoir models that recognise the challenges of simulating flow through systems with high permeability and scale contrasts and address the need for an ensemble of reservoir models to sufficiently cover geological uncertainties and their impact on fluid flow. In this work I developed several workflows for naturally fractured reservoir modelling that invite cross-disciplinary thinking by integrating geological uncertainties and dynamic data into the modelling procedure and foster ensemble modelling from the start. The workflows are tested on a synthetic field that is based upon a conceptual model for fold-related fracture distributions. The first workflow involves the use of multiple-point statistics to efficiently model reservoir-scale fracture distribution by upscaling discrete fracture networks and converting them into training images. To cover the impact of fracture-related geological uncertainties on fluid flow efficiently, flow diagnostics were used to screen and afterwards cluster and select training images according to their flow response for further reservoir modelling. The second workflow proposes a novel reservoir modelling technique that considers both static and dynamic data and utilises entropy to generate a diverse ensemble of reservoir models that all match an outset objective. Finally, an agent-based reservoir modelling workflow is introduced, where within a reservoir model, independent but interacting agents follow a set of rules to generate reservoir models that take into account geological prior information and expected dynamic flow responses to drive modelling efforts. Overall, we demonstrated that combining approaches from various disciplines into cross-disciplinary workflows provides great potential for subsurface characterisation. What workflow to adopt within a project, depends on various boundary conditions. The availability of data and time, the confidence in the understanding of the reservoir and the ultimate goal behind the modelling exercise. These factors can impact whether moving along with the simpler, more parametric multiple-point statistics workflow, the entropy-driven workflow that utilises static and dynamic data or the more data-driven agent-based modelling workflow is the right choice.James Watt Scholarshi

Formation Control and Reconfiguration Strategy of Multi-Agent Systems

Multi-agent systems consist of multiple agents, which detect and interact with their local environments. The formation control strategy is studied to drive multi-agent systems to predefined formations. The process is important because the objective formation is designed such that the group achieves more than the sum of its individuals. In this thesis, we consider formation control strategies and reconfiguration strategy for multi-agent systems. The main research contents are as follows. A formation control scheme is proposed for a group of elliptical agents to achieve a predefined formation. The agents are assumed to have the same dynamics, and communication among the agents limited. The desired formation is realized based on the reference formation and the mapping decision. In the controller design, searching algorithms for both cases of minimum distance and tangents are established for each agent and its neighbors. In order to avoid collision, an optimal path planning algorithm based on collision angles, and a self-center-based rotation algorithm are also proposed. Moreover, randomized method is used to provide the optimal mapping decision for the underlying system. To optimize the former formation control scheme, an adaptive formation control strategy is developed. The multiple elliptical agents can form a predefined formation in any 2D space. The controller is based on the neighborhood of each agent and the optimal mapping decision for the whole group. The collision-free algorithm is built based on direction and distance of avoidance group of each agent. The controller for each agent is adaptive based on the number of elements in its avoidance group, the minimum distance it has and its desired moving distance. The proposed adaptive mapping scheme calculates the repetition rate of optimal mappings in screening group of mapping decisions. The new optimal mapping is constructed by the fixed repeating elements in former mappings and the reorganized elements which are not the same in each optimal mappings based on the screening group. An event-triggered probability-driven control scheme is also investigated for a group of elliptical agents to achieve a predefined formation. The agents are assumed to have the same dynamics, and the control law for each agent is only updated at its event sequence based on its own minimum collision time and deviation time. The collision time of each agent is obtained based on the position and velocity of the others, and the deviation time is linked with the distance between its current position and desired position. The probabilitydriven controller is designed to prevent the stuck problem among agents. The stuck problem for the group means that when the distance between vi agents is too close and their moving directions are crossed, the control input with deterministic direction will cause the agents not to move or to move slowly. To optimize the event-triggered probability-driven controller, a mappingadaptive strategy and an angle-adaptive scheme are also developed. The mapping-adaptive strategy is used to find the optimal mapping to decrease the sum of the moving distance for the whole group, while the angle-adaptive scheme is employed to let the distance between any two elliptical agents is large enough to further ensure there is no collision existed during execution. Reconfiguration strategy is considered for multiple predefined formations. A two-stage reconfiguration strategy is proposed for a group of agents to find its special formation, which can be seen as transition of the predefined formations, during idle time in order to minimize the reconfiguration time. The basic reconfiguration strategy combines with a random mapping algorithm to find optimal special formation. To meet the practical requirements, agents are modeled as circles or ellipses. The anti-overlapping strategies are built to construct the achievable special formation based on the geometric properties of circle and ellipse.Thesis (Ph.D.) -- University of Adelaide, School of Electrical & Electronic Engineering, 202

Writing complexity: the American novel and systems realism

Although the relationship between literature and science has been a major focus of research in the last few decades, the influence of complex systems science on recent American fiction has not yet been comprehensively documented. I argue that a significant body of that fiction is systems-aware and thus represents the world as a network of complex systems. In the first section of the thesis, I claim that the origin of systems fiction can be found in the nineteenth-century social novel, which displayed significant knowledge of system function. Despite the narrative challenges posed by the complex, nonlinear structure of systems, contemporary authors somewhat surprisingly turn to a broadly traditional form of realism rather than experimental literary techniques. Motivated by the desire for social engagement, systems realism conceptualises systems as fundamentally ordered and thus narratable, though it acknowledges that this order is frequently inaccessible. In the second section, I engage in a close reading of systems-aware fiction and explore the extent to which novels incorporate the principles and discourse of systems science. I suggest that these novels seek to understand social concerns through analogy and the creation of fictional models which foreground structural homologies between systems. In the third and final section, I argue that systems-awareness is vital to an understanding of recent ‘post-postmodern’ paradigms, and I demonstrate this through an exploration of emerging trends in fiction which are shaped by systems thinking. In particular, I focus upon the emergence of environmental concerns in recent American writing. To explore the extent to which authors have perceived reality as systemic and have engaged with the representational challenges presented by complex systems provides us with new ways of thinking about the novel as a form. For these reasons I suggest that systems realism is central to the contemporary history of the novel