Hybrid Flocking Control Algorithm with Application to Coordination between Multiple Fixed-wing Aircraft

Flocking, as a collective behavior of a group, has been investigated in many areas, and in the recent decade, flocking algorithm design has gained a lot of attention due to its variety of potential applications. Although there are many applications exclusively related to fixed-wing aircraft, most of the theoretical works rarely consider these situations. The fixed-wing aircraft flocking is distinct from the general flocking problems by four practical concerns, which include the nonholonomic constraint, the limitation of speed, the collision avoidance and the efficient use of airspace. None of the existing works have addressed all these concerns. The major difficulty is to take into account the all four concerns simultaneously meanwhile having a relatively mild requirement on the initial states of aircraft. In this thesis, to solve the fixed-wing aircraft flocking problem, a supervisory decentralized control algorithm is proposed. The proposed control algorithm has a switching control structure, which basically includes three modes of control protocol and a state-dependent switching logic. Three modes of decentralized control protocol are designed based on the artificial potential field method, which helps to address the nonholonomic constraint, the limitation of speed and the collision avoidance for appropriate initial conditions. The switching logic is designed based on the invariance property induced by the control modes such that the desirable convergence properties of the flocking behavior and the efficient use of airspace are addressed. The proposed switching logic can avoid the fast mode switching, and the supervisor does not require to perform switchings frequently and respond to the aircraft immediately, which means the desired properties can still be guaranteed with the presence of the dwell time in the supervisor

Aggregation Pattern Transitions by Slightly Varying the Attractive/Repulsive Function

Among collective behaviors of biological swarms and flocks, the attractive/repulsive (A/R) functional links between particles play an important role. By slightly changing the cutoff distance of the A/R function, a drastic transition between two distinct aggregation patterns is observed. More precisely, a large cutoff distance yields a liquid-like aggregation pattern where the particle density decreases monotonously from the inside to the outwards within each aggregated cluster. Conversely, a small cutoff distance produces a crystal-like aggregation pattern where the distance between each pair of neighboring particles remains constant. Significantly, there is an obvious spinodal in the variance curve of the inter-particle distances along the increasing cutoff distances, implying a legible transition pattern between the liquid-like and crystal-like aggregations. This work bridges the aggregation phenomena of physical particles and swarming of organisms in nature upon revealing some common mechanism behind them by slightly varying their inter-individual attractive/repulsive functions, and may find its potential engineering applications, for example, in the formation design of multi-robot systems and unmanned aerial vehicles (UAVs)

Containment Control of Multiagent Systems with Multiple Leaders and Noisy Measurements

We consider the distributed containment control of multiagent systems with multiple stationary leaders and noisy measurements. A stochastic approximation type and consensus-like algorithm is proposed to solve the containment control problem. We provide conditions under which all the followers can converge both almost surely and in mean square to the stationary convex hull spanned by the leaders. Simulation results are provided to illustrate the theoretical results

Emergence of Structures in Particle Systems: Mechanics, Analysis and Computation

The meeting focused on the last advances in particle systems. The talks covered a broad range of topics, ranging from questions in crystallization and atomistic systems to mesoscopic models of defects to machine learning approaches and computational aspects

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

A Continuum Framework and Homogeneous Map Based Algorithms for Formation Control of Multi Agent Systems

In this dissertation, new algorithms for formation control of multi agent systems (MAS) based on continuum mechanics principles will be suggested. For this purpose, agents of the MAS are considered as particles in a continuum, evolving in R^n, whose desired configuration is required to satisfy an admissible deformation function. Considered is a specific class of mappings that are called homogenous where the Jacobian of the mapping is only a function of time and is not spatially varying. The primary objectives of this dissertation are to develop the necessary theory and its validation on a mobile-agent based swarm test bed that includes two primary tasks: 1) homogenous transformation of MAS and 2) deployment of a random distribution of agents on a desired configuration. Developed will be a framework based on homogenous transformations for the evolution of an MAS in an n-dimensional space (n=1,2, and 3), under1) no inter-agent communication (predefined motion plan), 2) local inter-agent communication, and 3) intelligent perception by agents. In this dissertation, different communication protocols for MAS evolution that are based on certain special features of a homogenous transformation will be developed. It is also aimed to deal with the robustness of tracking of a desired motion by an MAS evolving in R^n. Furthermore, the effect of communication delays in an MAS evolving under consensus algorithms or homogenous maps is investigated. In this regard, the maximum allowable communication delay for MAS evolution is formulated on the basis of eigen-analysis.Ph.D., Mechanical Engineering and Mechanics -- Drexel University, 201