The problem of coordinating construction vehicles in formations is tackled using the particle swarm optimization algorithm. Coordinated multi-vehicles are anticipated to outperform single vehicles in terms of economy and flexibility. A possible approach is to apply control theoretic methods to vehicle coordination but this may require complicated system models to be employed. The particle swarm...

Inspired by the phenomenon of symbiosis in natural ecosystems a multi-swarm cooperative particle swarm optimizer (MCPSO) is proposed as a new fuzzy modeling strategy for identification and control of non-linear dynamical systems. In MCPSO, the population consists of one master swarm and several slave swarms. The slave swarms execute particle swarm optimization (PSO) or its variants independentl...

In 2015, a group of Naval Postgraduate School (NPS) professors and students set the record for largest fixed-wing unmanned aerial vehicle (UAV) swarm flown at one time. The swarm had 50 vehicles flying simultaneously and successfully demonstrated distributed decision-making with all processing occurring on swarm vehicles rather than a centralized control station. Much of the decision-making is ...

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited rang...

Swarm intelligence deals with the study of collectively intelligent behavior that emerges from a decentralized system of non-intelligent individual agents. The concept is widely used in the fields of simulation, optimization or robotics, but less known in the domain of generative art. This paper presents the swarm paradigm in the context of artistic creation, and more particularly explores the ...

This paper presents a new optimization model – EPSO, Evolutionary Particle Swarm Optimization, inspired in both Evolutionary Algorithms and in Particle Swarm Optimization algorithms. The fundamentals of the method are described, and an application to the problem of Loss minimization and Voltage control is presented, with very good results.

This technical report describes how biologically inspired agents can be used to solve control and management problems in Telecommunications. These agents, inspired by the foraging behavior of ants, exhibit the desirable characteristics of simplicity of action and interaction. The collection of agents, or swarm system, deals only with local knowledge and exhibits a form of distributed control wi...

Social insects build extremely complex structures despite their limited perception and the absence of a global control system. Many of the structures built by termites can be construed as emergent phenomena driven by each worker’s reaction to local pheremone levels. This work extrapolates from termite building to a system for specifying swarm activity. In the system, swarms are homogeneous and ...

The design, operation and control of stabilization -tracking systems has been a challenging task for the scientists and engineers with the present day requirements of modern aged sophistication of these systems. The conventional control concepts have been outplayed by the optimal control techniques with the evolution of the modern control theory. Moreover, due to the problems associated with mo...