Search results

1 – 10 of 13
To view the access options for this content please click here
Article
Publication date: 2 October 2017

Shanjun Chen and Haibin Duan

The purpose of this paper is to propose an improved optimization method for image matching problem, which is based on multi-scale Gaussian mutation pigeon-inspired

Abstract

Purpose

The purpose of this paper is to propose an improved optimization method for image matching problem, which is based on multi-scale Gaussian mutation pigeon-inspired optimization (MGMPIO) algorithm, with the objective of accomplishing the complicated image matching quickly.

Design/methodology/approach

The hybrid model of multi-scale Gaussian mutation (MGM) mechanism and pigeon-inspired optimization (PIO) algorithm is established for image matching problem. The MGM mechanism is a nonlinear model, which can adjust the position of pigeons by mutation operation. In addition, the variable parameter (VP) mechanism is exploited to adjust the map and compass factor of the original PIO. Low-cost quadrotor, a type of electric multiple rotorcraft, is used as a carrier of binocular camera to obtain the images.

Findings

This work improved the PIO algorithm by modifying the search strategy and adding some limits, so that it can have better performance when applied to the image matching problem. Experimental results show that the proposed method demonstrates satisfying performance in convergence speed, robustness and stability.

Practical implications

The proposed MGMPIO algorithm can be easily applied to solve practical problems and accelerate convergence speed of the original PIO, and thus enhancing the speed of matching process, which will considerably increase the effectiveness of algorithm.

Originality/value

A hybrid model of the MGM mechanism and PIO algorithm is proposed for image matching problem. The VP mechanism and low-cost quadrotor is also utilized in image matching problem.

Details

Aircraft Engineering and Aerospace Technology, vol. 89 no. 6
Type: Research Article
ISSN: 1748-8842

Keywords

To view the access options for this content please click here
Article
Publication date: 15 November 2018

Siqi Li and Yimin Deng

The purpose of this paper is to propose a new algorithm for independent navigation of unmanned aerial vehicle path planning with fast and stable performance, which is…

Abstract

Purpose

The purpose of this paper is to propose a new algorithm for independent navigation of unmanned aerial vehicle path planning with fast and stable performance, which is based on pigeon-inspired optimization (PIO) and quantum entanglement (QE) theory.

Design/methodology/approach

A biomimetic swarm intelligent optimization of PIO is inspired by the natural behavior of homing pigeons. In this paper, the model of QEPIO is devised according to the merging optimization of basic PIO algorithm and dynamics of QE in a two-qubit XXZ Heisenberg System.

Findings

Comparative experimental results with genetic algorithm, particle swarm optimization and traditional PIO algorithm are given to show the convergence velocity and robustness of our proposed QEPIO algorithm.

Practical implications

The QEPIO algorithm hold broad adoption prospects because of no reliance on INS, both on military affairs and market place.

Originality/value

This research is adopted to solve path planning problems with a new aspect of quantum effect applied in parameters designing for the model with the respective of unmanned aerial vehicle path planning.

Details

Aircraft Engineering and Aerospace Technology, vol. 91 no. 1
Type: Research Article
ISSN: 1748-8842

Keywords

To view the access options for this content please click here
Article
Publication date: 4 March 2014

Haibin Duan and Peixin Qiao

The purpose of this paper is to present a novel swarm intelligence optimizer — pigeon-inspired optimization (PIO) — and describe how this algorithm was applied to solve…

Abstract

Purpose

The purpose of this paper is to present a novel swarm intelligence optimizer — pigeon-inspired optimization (PIO) — and describe how this algorithm was applied to solve air robot path planning problems.

Design/methodology/approach

The formulation of threat resources and objective function in air robot path planning is given. The mathematical model and detailed implementation process of PIO is presented. Comparative experiments with standard differential evolution (DE) algorithm are also conducted.

Findings

The feasibility, effectiveness and robustness of the proposed PIO algorithm are shown by a series of comparative experiments with standard DE algorithm. The computational results also show that the proposed PIO algorithm can effectively improve the convergence speed, and the superiority of global search is also verified in various cases.

Originality/value

In this paper, the authors first presented a PIO algorithm. In this newly presented algorithm, map and compass operator model is presented based on magnetic field and sun, while landmark operator model is designed based on landmarks. The authors also applied this newly proposed PIO algorithm for solving air robot path planning problems.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 7 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

To view the access options for this content please click here
Article
Publication date: 2 May 2017

Qiang Xue and Duan Haibin

The purpose of this paper is to propose a new approach for aerodynamic parameter identification of hypersonic vehicles, which is based on Pigeon-inspired optimization (PIO

Abstract

Purpose

The purpose of this paper is to propose a new approach for aerodynamic parameter identification of hypersonic vehicles, which is based on Pigeon-inspired optimization (PIO) algorithm, with the objective of overcoming the disadvantages of traditional methods based on gradient such as New Raphson method, especially in noisy environment.

Design/methodology/approach

The model of hypersonic vehicles and PIO algorithm is established for aerodynamic parameter identification. Using the idea, identification problem will be converted into the optimization problem.

Findings

A new swarm optimization method, PIO algorithm is applied in this identification process. Experimental results demonstrated the robustness and effectiveness of the proposed method: it can guarantee accurate identification results in noisy environment without fussy calculation of sensitivity.

Practical implications

The new method developed in this paper can be easily applied to solve complex optimization problems when some traditional method is failed, and can afford the accurate hypersonic parameter for control rate design of hypersonic vehicles.

Originality/value

In this paper, the authors converted this identification problem into the optimization problem using the new swarm optimization method – PIO. This new approach is proved to be reasonable through simulation.

Details

Aircraft Engineering and Aerospace Technology, vol. 89 no. 3
Type: Research Article
ISSN: 1748-8842

Keywords

To view the access options for this content please click here
Article
Publication date: 3 October 2016

Yongbin Sun, Ning Xian and Haibin Duan

The purpose of this paper is to propose a new algorithm for linear-quadratic regulator (LQR) controller of a quadrotor with fast and stable performance, which is based on…

Abstract

Purpose

The purpose of this paper is to propose a new algorithm for linear-quadratic regulator (LQR) controller of a quadrotor with fast and stable performance, which is based on pigeon-inspired optimization (PIO).

Design/methodology/approach

The controller is based on LQR. The determinate parameters are optimized by PIO, which is a newly proposed swarm intelligent algorithm inspired by the characteristics of homing pigeons.

Findings

The PIO-optimized LQR controller can obtain the optimized parameters and achieve stabilization in about 3 s.

Practical implications

The PIO-optimized LQR controller can be easily applied to the flight formation, autonomous aerial refueling (AAR) and detection of unmanned aerial vehicles, especially applied to (AAR) in this paper.

Originality/value

This research applies PIO to optimize the tuning parameters of LQR, which can considerably improve the fast and stabilizing performance of attitude control. The simulation results show the effectiveness of the proposed algorithm.

Details

Aircraft Engineering and Aerospace Technology, vol. 88 no. 6
Type: Research Article
ISSN: 1748-8842

Keywords

To view the access options for this content please click here
Article
Publication date: 4 January 2016

Rui Dou and Haibin Duan

The purpose of this paper is to propose a novel concept of model prediction control (MPC) parameter optimization method, which is based on pigeon-inspired optimization (PIO

Abstract

Purpose

The purpose of this paper is to propose a novel concept of model prediction control (MPC) parameter optimization method, which is based on pigeon-inspired optimization (PIO) algorithm, with the objective of optimizing the unmanned air vehicles (UAVs) controller design progress.

Design/methodology/approach

The PIO algorithm is proposed for parameter optimization in MPC, which provides a new method to get the optimal parameter.

Findings

The PIO algorithm is a new swarm optimization method, which consists of two operators, so it can be better adapted for the optimal problems. The comparative consequences results with the particle swarm optimization (PSO) demonstrate the effectiveness of the PIO algorithm, and the superiority for global search is also verified in various cases.

Practical implications

PIO algorithm can be easily applied to practice and help the parameter optimization of the MPC.

Originality/value

In this paper, we first present the concept of using the PIO algorithm for parameter optimization in MPC so as to achieve the global best optimization. By using the PIO algorithm, the choice of the parameter could be easier and more effective. The authors also applied the algorithm to the designing of the MPC controller to optimize the response of the pitch rate of UAV.

Details

Aircraft Engineering and Aerospace Technology: An International Journal, vol. 88 no. 1
Type: Research Article
ISSN: 0002-2667

Keywords

To view the access options for this content please click here
Article
Publication date: 14 March 2016

Zhengxuan JIA

With increasing demand of localization service in challenging environments where Global Navigation Satellite Systems (GNSS) signals are considerably weak, a powerful…

Abstract

Purpose

With increasing demand of localization service in challenging environments where Global Navigation Satellite Systems (GNSS) signals are considerably weak, a powerful approach, the collective detection (CD), has been developed. However, traditional CD techniques are computationally intense due to the large clock bias search space. Therefore, the purpose of this paper is to develop a new scheme of CD with less computational burden, in order to accelerate the detection and location process.

Design/methodology/approach

This paper proposes a new scheme of CD. It reformulates the problem of GNSS signal detection as an optimization problem, and solves it with the aid of an improved Pigeon-Inspired Optimization (PIO). With the improved PIO algorithm adopted, the positioning algorithm arrives to evaluate only a part of the points in the search space, avoiding the problems of grid-search method which is universally adopted.

Findings

Faced with the complex optimization problem, the improved PIO algorithm proves to have good performance. In the acquisition of simulated and real signals, the proposed scheme of CD with the improved PIO algorithm also have better efficiency, precision and stability than traditional CD algorithm. Besides, the improved PIO algorithm also proves to be a better candidate to be integrated into the proposed scheme than particle swarm optimization, differential evolution and PIO.

Originality/value

The novelty associated with this paper is the proposition of the new scheme of CD and the improvement of PIO algorithm. Thus, this paper introduces another possibility to ameliorate the traditional CD.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 9 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

To view the access options for this content please click here
Article
Publication date: 26 March 2021

Bing Hua, Nan Zhang and Mohong Zheng

Taking into account the factors of torque saturation and angular velocity limitation during the actual attitude maneuver of the satellite, as well as the difficulty of…

Abstract

Purpose

Taking into account the factors of torque saturation and angular velocity limitation during the actual attitude maneuver of the satellite, as well as the difficulty of parameter selection in the design of attitude control algorithm, the purpose of this paper is to propose a satellite magnetic/momentum wheel attitude control technology based on pigeon-inspired optimization (PIO) cascade-saturation control law optimization.

Design/methodology/approach

The optimal parameters are calculated through the PIO algorithm and then the parameters are used in the cascade-saturation control law to control the actuator findings-mathematical simulation results show that the cascade-saturation control law optimization algorithm based on PIO can shorten the adjustment time and reduce the steady-state error.

Findings

Compared with traditional attitude maneuver control with given parameters, the PIO algorithm can accurately calculate the optimal parameters needed to achieve the control objective and this method has better stability and higher accuracy.

Originality/value

The innovative PIO algorithm is used to calculate the optimal parameters, and the cascade saturation control law is used to control the actuator. Compared with the traditional algorithm, the regulation time is shortened and the steady-state error is reduced.

Details

World Journal of Engineering, vol. 18 no. 4
Type: Research Article
ISSN: 1708-5284

Keywords

To view the access options for this content please click here
Article
Publication date: 2 October 2017

Daifeng Zhang, Haibin Duan and Yijun Yang

The purpose of this paper is to propose a control approach for small unmanned helicopters, and a novel swarm intelligence algorithm is used to optimize the parameters of…

Abstract

Purpose

The purpose of this paper is to propose a control approach for small unmanned helicopters, and a novel swarm intelligence algorithm is used to optimize the parameters of the proposed controller.

Design/methodology/approach

Small unmanned helicopters have many advantages over other unmanned aerial vehicles. However, the manual operation process is difficult because the model is always instable and coupling. In this paper, a novel optimized active disturbance rejection control (ADRC) approach is presented for small unmanned helicopters. First, a linear attitude model is built in hovering condition according to small perturbation linearization. To realize decoupling, this model is divided into two parts, and each part is equipped with an ADRC controller. Finally, a novel Levy flight-based pigeon-inspired optimization (LFPIO) algorithm is developed to find the optimal ADRC parameters and enhance the performance of controller.

Findings

This paper applies ADRC method to the attitude control of small unmanned helicopters so that it can be implemented in practical flight under complex environments. Besides, a novel LFPIO algorithm is proposed to optimize the parameters of ADRC and is proved to be more efficient than other homogenous methods.

Research limitations/implications

The model of proposed controller is built in the hovering action, whereas it cannot be used in other flight modes.

Practical implications

The optimized ADRC method can be implemented in actual flight, and the proposed LFPIO algorithm can be developed in other practical optimization problems.

Originality/value

ADRC method can enhance the response and robustness of unmanned helicopters which make it valuable in actual environments. The proposed LFPIO algorithm is proved to be an effective swarm intelligence optimizer, and it is convenient and valuable to apply it in other optimized systems.

Details

Aircraft Engineering and Aerospace Technology, vol. 89 no. 6
Type: Research Article
ISSN: 1748-8842

Keywords

To view the access options for this content please click here
Article
Publication date: 14 August 2017

Ning Xian

The purpose of this paper is to propose a new algorithm chaotic pigeon-inspired optimization (CPIO), which can effectively improve the computing efficiency of the basic…

Abstract

Purpose

The purpose of this paper is to propose a new algorithm chaotic pigeon-inspired optimization (CPIO), which can effectively improve the computing efficiency of the basic Itti’s model for saliency-based detection. The CPIO algorithm and relevant applications are aimed at air surveillance for target detection.

Design/methodology/approach

To compare the improvements of the performance on Itti’s model, three bio-inspired algorithms including particle swarm optimization (PSO), brain storm optimization (BSO) and CPIO are applied to optimize the weight coefficients of each feature map in the saliency computation.

Findings

According to the experimental results in optimized Itti’s model, CPIO outperforms PSO in terms of computing efficiency and is superior to BSO in terms of searching ability. Therefore, CPIO provides the best overall properties among the three algorithms.

Practical implications

The algorithm proposed in this paper can be extensively applied for fast, accurate and multi-target detections in aerial images.

Originality/value

CPIO algorithm is originally proposed, which is very promising in solving complicated optimization problems.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

1 – 10 of 13