Particle Swarm Optimization for Test Case Prioritization Using String Distance

2018 ◽  
Vol 24 (10) ◽  
pp. 7221-7226
Author(s):  
Muhammad Khatibsyarbini ◽  
Mohd Adham Isa ◽  
Dayang Norhayati Abang Jawawi
2020 ◽  
Vol 92 (8) ◽  
pp. 1281-1293
Author(s):  
Khurram Shahzad Sana ◽  
Weiduo Hu

Purpose The aim of this study is to design a guidance method to generate a smoother and feasible gliding reentry trajectory, a highly constrained problem by formalizing the control variables profile. Design/methodology/approach A novel accelerated fractional-order particle swarm optimization (FAPSO) method is proposed for velocity updates to design the guidance method for gliding reentry flight vehicles with fixed final energy. Findings By using the common aero vehicle as a test case for the simulation purpose, it is found that during the initial phase of the longitudinal guidance, there are oscillations in the state parameters which cause to violate the path constraints. For the glide phase of the longitudinal guidance, the path constraints have higher values because of the increase in the atmosphere density. Research limitations/implications The violation in the path constraints may compromise the flight vehicle safety, whereas the enforcement assures the flight safety by flying it within the reentry corridor. Originality/value An oscillation suppression scheme is proposed by using the FAPSO method during the initial phase of the reentry flight, which smooths the trajectory and enforces the path constraints partially. To enforce the path constraints strictly in the glide phase, ultimately, another scheme by using the FAPSO method is proposed. The simulation results show that the proposed algorithm is efficient to achieve better convergence and accuracy for nominal as well as dispersed conditions.


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