ABSTRACT: In this paper, a new form of open traveling salesman problem (OTSP) is used for path planning for optimal coverage of a wide area by cooperated unmanned aerial vehicles (UAVs). A hybrid form of particle swarm optimization (PSO) and genetic algorithm (GA) is developed for the current path planning problem of multiple UAVs in the coverage mission. Three path-planning approaches are introduced through a group of the waypoints in a mission area: PSO, genetic algorithm, and a hybrid form of parallel PSO-genetic algorithm. The proposed hybrid optimization tries to integrate the advantages of the PSO, i.e. coming out from local minimal, and genetic algorithm, i.e. better quality solutions within a reasonable computational time. These three approached are compared in many scenarios with different levels of difficulty. Statistical analyses reveal that the hybrid algorithm is a more effective strategy than others for the mentioned problem.

Abstract: The effects of different mixing, bamboo mesh size and heat treatment on the physical and mechanical properties and biodegradability of a polylactic acid (PLA) composite were determined. The results indicated that this composite exhibited high strength in all mechanical properties examined, except hardness using the pure polymer (PLA). The mesh size of the bamboo flour and heat treatment had considerable effects on all tests expect the decay resistance. The water absorbance and thickness swelling of the PLA composite was reduced to nearly zero after 3000 hours immersion in water. Moreover, the fungal decay test results demonstrated that PLA was highly resistant to both Basidiomycetes and Ascomycetes fungi. The brown rot fungi, however, produced an extensive mass loss in the composite composed of different levels of bamboo flour.

ABSTRACT The structure of mission management and maneuver planning for multiple UAVs in close formation flight is investigated. This article provides a distributed and priority-based platform of guidance and control model to meet requirements for each coordinated maneuver. To accomplish the coordinated maneuvers of multiple UAVs, some levels of hierarchy from mission planning to accurate guidance law are presented. The main focuses have been on the structure of equations and vicinity pattern to avoid a probable collision during maneuver so the high-level decision-maker can integrate all irregularities and solve them at the same time. Unlike complex control systems, the proposed algorithm provides outstanding following performance and inherent collision avoidance pattern due to prioritized tracking. The results show the admissible performance of the framework designed for implementing coordinated maneuvers due to its lower collision probability and noise resistance. According to the simulations, this method also resolves irregularity and disarrangements in the close formation flights and tracking media.

An n × n real matrix P is said to be a generalized reflection matrix if P T = P and P² = I (where P T is the transpose of P). A matrix A ∈ Rn×n is said to be a reflexive (anti-reflexive) matrix with respect to the generalized reflection matrix P if A = P A P (A = - P A P). The reflexive and anti-reflexive matrices have wide applications in many fields. In this article, two iterative algorithms are proposed to solve the coupled matrix equations { A1 XB1 + C1X T D1 = M1. A2 XB2 + C2X T D2 = M2. over reflexive and anti-reflexive matrices, respectively. We prove that the first (second) algorithm converges to the reflexive (anti-reflexive) solution of the coupled matrix equations for any initial reflexive (anti-reflexive) matrix. Finally two numerical examples are used to illustrate the efficiency of the proposed algorithms. Mathematical subject classification: 15A06, 15A24, 65F15, 65F20.

Finding the zeros of a nonlinear equation ƒ (x) = 0, is a classical problem which has nice applications in various branches of science and engineering. In this paper, we introduce four iterative methods which is based on the central-difference and forward-difference approximations to derivatives. It is proved that three of the four methods have cubic convergence and another method has quadratic convergence. The best property of these methods are that do not need to calculate any derivative. In order to demonstrate convergence properties of the introduced methods, several numerical examples are given.