Abstract: In this paper, a Cooperative Multi-robot for Carrying
Targets (CMCT) algorithm is proposed. The multi-robot team
consists of three robots, one is a supervisor and the others are
workers for carrying boxes in a store of 100×100 m2. Each robot has
a self recharging mechanism. The CMCT minimizes robot-s worked
time for carrying many boxes during day by working in parallel. That
is, the supervisor detects the required variables in the same time
another robots work with previous variables. It works with
straightforward mechanical models by using simple cosine laws. It
detects the robot-s shortest path for reaching the target position
avoiding obstacles by using a proposed CMCT path planning
(CMCT-PP) algorithm. It prevents the collision between robots
during moving. The robots interact in an ad hoc wireless network.
Simulation results show that the proposed system that consists of
CMCT algorithm and its accomplished CMCT-PP algorithm
achieves a high improvement in time and distance while performing
the required tasks over the already existed algorithms.
Abstract: To maximise furnace production it-s necessary to
optimise furnace control, with the objectives of achieving maximum
power input into the melting process, minimum network distortion
and power-off time, without compromise on quality and safety. This
can be achieved with on the one hand by an appropriate electrode
control and on the other hand by a minimum of AC transformer
switching.
Electrical arc is a stochastic process; witch is the principal cause
of power quality problems, including voltages dips, harmonic
distortion, unbalance loads and flicker. So it is difficult to make an
appropriate model for an Electrical Arc Furnace (EAF). The factors
that effect EAF operation are the melting or refining materials,
melting stage, electrode position (arc length), electrode arm control
and short circuit power of the feeder. So arc voltages, current and
power are defined as a nonlinear function of the arc length. In this
article we propose our own empirical function of the EAF and model,
for the mean stages of the melting process, thanks to the
measurements in the steel factory.