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Content Provider | IET Digital Library |
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Author | Wang, Hongfei Li, Yongwei |
Abstract | A hybrid modified teaching–learning-based particle swarm optimisation (HMTL-PSO) initialised by the normalised step cost (NSC), named HMTL-NSCPSO, is proposed for solving trajectory optimisation with complex constraint problems. Specially, the new HMTL-NSCPSO combines the canonical PSO basic policy, the teaching–learning-based optimisation (TLBO) algorithm and the normalised step cost (NSC) function in order to promote diversity, obtain well-speed convergence and to improve search ability. The algorithm is tested on an UAV trajectory optimization problems. Experimental results validate the effectiveness of the HMTL-NSCPSO. |
Starting Page | 777 |
Ending Page | 779 |
Page Count | 3 |
ISSN | 00135194 |
Volume Number | 53 |
e-ISSN | 1350911X |
Issue Number | Issue 12, Jun (2017) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/el/53/12 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/el.2017.0729 |
Journal | Electronics Letters |
Publisher Date | 2017-05-09 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Aerospace Control Autonomous Aerial Vehicle Canonical PSO Basic Policy Complex Constraint Problem HMTL-NSCPSO Hybrid Modified Teaching-learning-based PSO Normalised Step Cost Function Optimal Control Optimisation Technique Other Topics in AeroSpace Particle Swarm Optimisation Search Ability Spatial Variables Control TLBO Algorithm Trajectory Optimisation Trajectory Optimisation (aeroSpace) UAV Trajectory Optimisation Problem |
Content Type | Text |
Resource Type | Article |
Subject | Electrical and Electronic Engineering |
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