This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was impleme...

The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle ...

In this article, an automatic vehicle parallel parking algorithm, consisting of path planning, controller design, and state estimation is developed. The planned using clothoid sequences a straight line, which avoids stopping the car to reorient wheels. control inputs, including speed steering angle, are function traveled distance. This method enables park from different initial poses, achieving...

Abstract Multi-objective particle swarm optimization algorithms encounter significant challenges when tackling many-objective problems. This is mainly because of the imbalance between convergence and diversity that occurs increasing selection pressure. In this paper, a novel adaptive MOPSO (ANMPSO) algorithm based on R2 contribution method developed to improve performance MOPSO. First, new glob...

Aiming at industrial organization multi-objective optimization problem in Equipment Manufacturing Industry, The paper proposes a new type of double layer evolutionary cultural particle swarm optimization algorithm. The algorithm combines the advantages of the particle swarm optimization algorithm and cultural algorithm. It not only revises the problem that the particles are easy to “premature”,...