Formation control of non-identical multi-agent systems

The problem considered in this work is formation control for non-identical linear multi-agent systems (MASs) under a time-varying communication network. The size of the formation is scalable via a scaling factor determined by a leader agent. Past works on scalable formation are limited to identical agents under a fixed communication network. In addition, the formation scaling variable is updated under a leader-follower network. Differently, this work considers a leaderless undirected network in addition to a leader-follower network to update the formation scaling variable. The control law to achieve scalable formation is based on the internal model principle and consensus algorithm. A biased reference output, updated in a distributed manner, is introduced such that each agent tracks a different reference output. Numerical examples show the effectiveness of the proposed method

Distributed formation stabilization for mobile agents using virtual tensegrity structures

This paper investigates the distributed formation control problem for a group of mobile Euler-Lagrange agents to achieve global stabilization by using virtual tensegrity structures. Firstly, a systematic approach to design tensegrity frameworks is elaborately explained to confine the interaction relationships between agents, which allows us to obtain globally rigid frameworks. Then, based on virtual tensegrity frameworks, distributed control strategies are developed such that the mobile agents converge to the desired formation globally. The theoretical analysis is further validated through simulations

Adaptive Formation Control of Cooperative Multi-Vehicle Systems

The literature comprises many approaches and results for the formation control of multi-vehicle systems; however, the results established for the cases where the vehicles contain parametric uncertainties are limited. Motivated by the need for explicit characterization of the effects of uncertainties on multi-vehicle formation motions, we study distributed adaptive formation control of multi-vehicle systems in this thesis, focusing on different interrelated sub-objectives. We first examine the cohesive motion control problem of minimally persistent formations of autonomous vehicles. Later, we consider parametric uncertainties in vehicle dynamics in such autonomous vehicle formations. Following an indirect adaptive control approach and exploiting the features of the certainty equivalence principle, we propose control laws to solve maneuvering problem of the formations, robust to parametric modeling uncertainties. Next, as a formation acquisition/closing ranks problem, we study the adaptive station keeping problem, which is defined as positioning an autonomous mobile vehicle $A$ inside a multi-vehicle network, having specified distances from the existing vehicles of the network. In this setting, a single-integrator model is assumed for the kinematics for the vehicle $A$, and $A$ is assumed to have access to only its own position and its continuous distance measurements to the vehicles of the network. We partition the problem into two sub-problems; localization of the existing vehicles of the network using range-only measurements and motion control of $A$ to its desired location within the network with respect to other vehicles. We design an indirect adaptive control scheme, provide formal stability and convergence analysis and numerical simulation results, demonstrating the characteristics and performance of the design. Finally, we study re-design of the proposed station keeping scheme for the more challenging case where the vehicle $A$ has non-holonomic motion dynamics and does not have access to its self-location information. Overall, the thesis comprises methods and solutions to four correlated formation control problems in the direction of achieving a unified distributed adaptive formation control framework for multi-vehicle systems