This paper describes a novel control scheme termed ‘equilibrium shaping’ for the control of a swarm of spacecraft in both flat and curved space. This control scheme allows the intelligent and autonomous control of an arbitrary number of elements, suitable for example to self-assembly or formation flying applications. The control scheme employs three basis behaviours that are summed together to ...

This paper presents an intelligent approach to identify parameters of single-phase induction motors. Because of the complication of space-phasor equations describing its dynamic behaviors, the parameters of single-phase induction motors could be roughly estimated via conventional tests based on the steady-state analysis. Therefore, they may cause inaccurate estimation. In this paper, some effic...

For a decade swarm Intelligence is concerned with the design of intelligent systems by taking inspiration from the collective behaviors of social insects. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. This paper focuses on the procedure of most successful methods of optimization techniques inspired by Swarm Intelligence: Ant Colony Optimization (ACO) and P...

The work reported in this paper proposes a Swarm-Array computing approach based on ’Intelligent Agents’ to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a swarm robotics inspired, novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent ...

Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees’ swarming around their hive is another example of swarm intelligence. Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behavio...

Early studies in particle swarm optimization (PSO) algorithm reveal that the social and cognitive components of swarm, i.e. memory swarm, tend to distribute around the problem's optima. Motivated by these findings, we propose a two-layer PSO with intelligent division of labor (TLPSO-IDL) that aims to improve the search capabilities of PSO through the evolution memory swarm. The evolution in TLP...

In this work we present the hardware architecture of a mobile heterogeneous robot swarm, designed and implemented at the Interdisciplinary Robotics, Intelligent Sensing and Control (RISC) Laboratory, University of Bridgeport. Most of the recent advances in swarm robotics have mainly focused on homogeneous robot swarms and their applications. Developing and coordinating a multi-agent robot syste...