Target detection approach for UAVs via improved Pigeon-inspired Optimization and Edge Potential Function

Li, Cong; Duan, Haibin

doi:10.1016/j.ast.2014.10.007

Cited by 74 publications

(24 citation statements)

References 19 publications

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“…The control board then takes necessary data from the sensors and processes them with the input signals. Output signals are then generated from this in- put data and sent to the ESCs which in turn controls the speed of the motors [22][23][24].…”

Section: Controlmentioning

confidence: 99%

Flying by the Sun only: The Solarcopter prototype

Shaheed

Abidali

Ahmed

et al. 2015

Aerospace Science and Technology

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Section: Controlmentioning

confidence: 99%

Flying by the Sun only: The Solarcopter prototype

Shaheed

Abidali

Ahmed

et al. 2015

Aerospace Science and Technology

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“…Whether in orbital spacecraft formation reconfiguration [17] or in target detection task [18], PIO has made a better performance than other well-known rivals, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) optimization. It is undeniable that PIO has some advantages in some mono-objective optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design

Qiu

Duan

2015

Sci. China Technol. Sci.

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Pigeon-inspired optimization (PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. A variant of pigeon-inspired optimization named multi-objective pigeon-inspired optimization (MPIO) is proposed in this paper. It is also adopted to solve the multi-objective optimization problems in designing the parameters of brushless direct current motors, which has two objective variables, five design variables, and five constraint variables. Furthermore, comparative experimental results with the modified non-dominated sorting genetic algorithm are given to show the feasibility, validity and superiority of our proposed MIPO algorithm. brushless direct current (BLDC) motor, multi-objective pigeon-inspired optimization (MPIO), electromagnetics, multi-objective optimization Citation:Qiu H X, Duan H B. Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design.

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“…In nature, pigeons search their home or destination mainly by three tools: the magnetic field, the sun and landmarks. Inspired by the natural phenomena, the PIO algorithm utilizes two operators to describe the behavior of pigeons [18][19][20][21]. Each pigeon represents a candidate solution of the problem.…”

Section: Introductionmentioning

confidence: 99%

Hybrid membrane computing and pigeon-inspired optimization algorithm for brushless direct current motor parameter design

Deng

Zhu

Duan

2016

Sci. China Technol. Sci.

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In this paper, a novel approach is proposed for solving the parameter design problem of brushless direct current (BLDC) motor, which is based on the membrane computing (MC) and pigeon-inspired optimization (PIO) algorithm. The motor parameter design problem is converted to an optimization problem with five design parameters and six constraints. The PIO algorithm is introduced into the framework of MC for improving the global convergence performance. The hybrid algorithm can improve the population diversity with better searching efficiency. Comparative simulations are conducted, and comparative results are given to show the feasibility and effectiveness of our proposed hybrid algorithm for high nonlinear optimization problems. brushless direct current (BLDC) motor, pigeon-inspired optimization (PIO), membrane computing (MC) Citation:Deng Y M, Zhu W R, Duan H B. Hybrid membrane computing and pigeon-inspired optimization algorithm for brushless direct current motor parameter design.

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Target detection approach for UAVs via improved Pigeon-inspired Optimization and Edge Potential Function

Cited by 74 publications

References 19 publications

Flying by the Sun only: The Solarcopter prototype

Flying by the Sun only: The Solarcopter prototype

Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design

Hybrid membrane computing and pigeon-inspired optimization algorithm for brushless direct current motor parameter design

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