Veysel Gazi

Coordination and control of multi-agent dynamic systems: models and approaches

The field of multi-agent dynamic systems is an inter-disciplinary research field that has become very popular in the recent years in parallel with the significant interest in the practical applications of such systems in various areas including robotics. In this article we give a relatively short review of this field from the system dynamics and control perspective. We first focus on mathematical modelling of multi-agent systems paying particular attention on the agent dynamics models available in the literature. Then we present a number of problems on coordination and control of multi-agent systems which have gained significant attention recently and various approaches to these problems. Relevant to these problems and approaches, we summarize some of the recent results on stability, robustness, and performance of multi-agent dynamic systems which appeared in the literature. The article is concluded with some remarks on the implementation and application side of the control designs developed for multi-agent systems.

Stability of an Asynchronous Swarm With Time-Dependent Communication Links

In this correspondence, we consider a simple model of interacting agents with fixed or time-dependent communication links. We allow for asynchronous operation and time delays in the information flow. We show that the convergence of the states of the agents to a common value will be achieved, provided that old information is uniformly purged from the system. The considered model finds an application not only in swarming but also in other fields, including synchronization and distributed decision making or consensus seeking.

Particle swarm optimization with dynamic neighborhood topology: Three neighborhood strategies and preliminary results

In this article we consider a particle swarm optimization (PSO) algorithm in which the neighbors of the particles or basically the neighborhood topology dynamically changes with time. We consider probabilistic and distance based approaches for determining the neighbors of the particles and represent the dynamic neighborhood topology by a time varying graph. Simulations of several benchmark functions are performed in order to verify the effectiveness of the algorithm.

Single-View Distance-Estimation-Based Formation Control of Robotic Swarms

This paper presents a practical formation motion control scheme for robotic swarms based on single-view distance estimation, which is performed using a single nonsophisticated camera on each robot agent, and the prior information about the heights of the robots and other objects in the environment. Here, a nonsophisticated camera means one that has limited field of view and limited resolution. First, the vision mechanism is analyzed, and a single-view distance estimation scheme is designed. Then, a set of decentralized control laws, to be incorporated with distance estimation scheme, is introduced to move the robotic swarm in formation from an arbitrary initial position to an arbitrary final position without deforming the formation shape. The robots do not have any global positioning sensors, and they do not communicate with each other. The stability and performance of the overall system are analyzed mathematically. Later, practical issues are discussed regarding the proposed scheme, and the effects of delay and quantization in distance estimation are formally analyzed. Finally, we present experimental results demonstrating the performance of the proposed control scheme in real time.

Stability of a one-dimensional discrete-time asynchronous swarm

In this correspondence, we consider a discrete time one-dimensional asynchronous swarm. First, we describe the mathematical model for motions of the swarm members. Then, we analyze the stability properties of that model. The stability concept that we consider, which matches exactly with stability of equilibria in control theory, characterizes stability of a particular position (relative arrangement) of the swarm members. We call that position the comfortable position (with comfortable intermember distances). Our swarm model and stability analysis are different from other asynchronous swarm models considered in the literature. In particular, in our analysis we employ results on contractive mappings from the parallel and distributed computation literature. The application of these results to the swarm coordination problem is important by itself since they might prove useful also in n-dimensional swarms.

Swarm Tracking Using Artificial Potentials and Sliding Mode Control

In this paper, we present a stable and decentralized control strategy for multiagent systems (swarms) to capture a moving target in a specific formation. The coordination framework uses artificial potentials to take care of both tracking and formation tasks. First, a basic controller is designed based on a kinematic model. After that, sliding mode control technique is used to force the agents with general vehicle dynamics to obey the required motion. Finally, specific potential functions are discussed and corresponding simulation results are given.

Stability analysis of social foraging swarms: combined effects of attractant/repellent profiles

In this paper we study the stability of the collective behavior of social foraging swarms, i.e., swarms moving in a profile of nutrient/toxic substances (an attractant/repellent profile) and extend our previous results. In particular, we consider a plane profile and also extend our results for the quadratic, Gaussian, and multi-modal Gaussian profiles. Moreover, we analyze the ultimate behavior of the individuals in the social foraging swarm. The paper closes with new simulation studies that give insights into swarm dynamics.

Decentralized asynchronous particle swarm optimization

In this article we discuss a decentralized totally asynchronous realization of the particle swarm optimization (PSO) algorithm, which is suitable for parallel implementation. The proposed method has important differences from the PSO implementations considered in the literature. In the proposed method the particles are allowed to exchange information and to update their estimates at totally independent time instants. Moreover, time delays during information exchange between particles (leading to use of outdated information) are also allowed. Furthermore, particle neighborhoods are allowed to dynamically change with time. We also provide a mathematical model of the proposed method based on results in the parallel and distributed computation literature. The performance of the proposed algorithm is tested using numerical simulations with benchmark functions.

Output regulation of a class of linear systems with switched exosystems

In this article we investigate the output regulation (servomechanism) problem of linear systems with external inputs generated by switched linear systems. We use switching controllers and consider both the full information and the error feedback controllers under the assumption that there is a synchronization between exosystem and controller switching.

Stochastic stability analysis of the particle dynamics in the PSO algorithm

In this article we analyze the stability of the particle dynamics in the Particle Swarm Optimization algorithm using tools from the nonlinear control systems literature including positive realness and stability of stochastic systems.