Path Planning for an HEXA Parallel Mechanism using a Modified PSO Algorithm

This paper presents a method for determining the optimal trajectory of the characteristic point based on the kinematic analysis of a HEXA parallel mechanism. The optimization was performed based on a modified PSO algorithm based on Hermite polynomials (MH-PSO). The change made to the initial algorithm consists in restricting the search space of the solutions by using the Hermite polynomial expressions of the geometric parameters as time functions for defining the movements of the end-effector. The MH-PSO algorithm, from its inception, ensures a faster convergence of solutions and ease of computational effort and is the main advantage of the method presented. During the optimization process, the function followed was the length of the trajectory described by the sequence of positions of the characteristic point, belonging to the end effector element, in compliance with additional conditions imposed. The use of the Hermite functions and PSO algorithm leads to minimal effort for analysis and mathematical formulation of the optimization problem.

Optimized Traffic Grooming through modified PSO based Iterative Hungarian algorithm in Optical Networks

Due to huge size of the data and quick transmission of data between the nodes present in the optical network, a condition of network traffic is created among the nodes of the network. This issue of traffic can be overcome by employing numerous traffic grooming techniques. In this research paper, the best suitable shortest path is determined by the multi objective modified PSO algorithm and an innovative visibility graph based Iterative Hungarian Traffic grooming algorithm is implemented to reduce the blocking ratio through improving the allocation of bandwidth between the users. Then finally the performance analysis is carried out by means of performance measures such as traffic throughput, transceivers count, average propagation delay, blocking ratio, and success ratio. It can be inferred that the proposed work obtains enhanced outcomes when compared to the other existing techniques.

A novel optimization of the particle swarm based maximum power point tracking for photovoltaic systems under partially shaded conditions

<p><span lang="EN-US">When the irradiance distribution over the photovoltaic panels is uniform, the pursuit of the maximum power point is not reached, which has allowed several researchers to use traditional MPPT techniques to solve this problem Among these techniques a PSO algorithm is used to have the maximum global power point (GMPPT) under partial shading. On the other hand, this one is not reliable vis-à-vis the pursuit of the MPPT. Therefore, in this paper we have treated another technique based on a new modified PSO algorithm so that the power can reach its maximum point. The PSO algorithm is based on the heuristic method which guarantees not only the obtaining of MPPT but also the simplicity of control and less expensive of the system. The results are obtained using MATLAB show that the proposed modified PSO algorithm performs better than conventional PSO and is robust to different partial shading models.</span></p>

On the Efficacy of Particle Swarm Optimization for Gateway Placement in LoRaWAN Networks

The efficacy of the Particle Swarm Optimization (PSO) in determining the optimal locations for gateways in LoRaWAN networks is investigated. A modified PSO approach, which introduces gateway distancing measures during the initialization phase and flight time, is proposed. For the ease of comparisons and the understanding of the behavior of the algorithms under study, a square LoRaWAN area is used for simulations. Optimization results on a LoRaWAN script, implemented in NS-3, show that the modified PSO converges faster and achieves better results than the traditional PSO, as the number of gateways increases. Results further show that the modified PSO approach achieves similar performance to a deterministic approach, in which gateways are uniformly distributed in the network. This shows that for swarm intelligence techniques such as PSO to be used for gateway placement in LoRaWAN networks, gateway distancing mechanisms must be incorporated in the optimization process. These results further show that these techniques can be easily deployed in geometrically more complex LoRaWAN figures such as rectangular, triangular, circular and trapezoidal shapes. It is generally difficult to figure out a deterministic gateway placement mechanism for such shapes. As part of future work, more realistic LoRaWAN networks will be developed by using real geographical information of an area.