Detection of multiple source locations using a glowworm metaphor with applications to collective robotics

This paper presents a glowworm swarm based algorithm that finds solutions to optimization of multiple optima continuous functions. The algorithm is a variant of a well known ant-colony optimization (ACO) technique, but with several significant modifications. Similar to how each moving region in the ACO technique is associated with a pheromone value, the agents in our algorithm carry a luminescence quantity along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luminescence and have a circular sensor range. The glowworms depend on a local-decision domain to compute their movements. Simulations demonstrate the efficacy of the proposed glowworm based algorithm in capturing multiple optima of a multimodal function. The above optimization scenario solves problems where a collection of autonomous robots is used to form a mobile sensor network. In particular, we address the problem of detecting multiple sources of a general nutrient profile that is distributed spatially on a two dimensional workspace using multiple robots.

Developement of DSP based educational kit for power electronics and drives

The educational kit was developed for power electronics and drives. The need and purpose of this kit is to train engineers with current technology of digital control in power electronics. The DSP is the natural choice as it is able to perform high speed calculations required in power electronics. The educational kit consists of a DSP platform using TI DSP TMS320C50 starter kit, an inverter and an induction machine-dc machine set. A set of experiments have been prepared so that DSP programming can be learned easily in a smooth fashion. Here the application presented is open loop V/F control of three phase induction using sine pulse width modulation technique.