To overcome the ambiguity of the location information of wireless sensor network nodes and lead to the low accuracy of weighted centroid localisation results, a new weighted centroid correction method based on group s...
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To overcome the ambiguity of the location information of wireless sensor network nodes and lead to the low accuracy of weighted centroid localisation results, a new weighted centroid correction method based on group search optimiser (gso) algorithm for wireless sensor networks is proposed in this paper. This method randomly drops sensor nodes into the area to be monitored to form a wireless sensor network. The experimental results show that the network coverage is close to 100%, the energy consumption per unit during receiving and transmitting accounts for 0.31% of the total battery. The absolute positioning error of each node is 6-8.5 m, which can achieve the expected goal of this study.
A kind of attitude control strategy for the quadrotor based on active disturbance rejection control (ADRC) is proposed in this paper. Firstly, the dynamic model using Newton -Eulerformula of the quadrotor helicopter i...
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ISBN:
(纸本)9781538612446
A kind of attitude control strategy for the quadrotor based on active disturbance rejection control (ADRC) is proposed in this paper. Firstly, the dynamic model using Newton -Eulerformula of the quadrotor helicopter is developed. Then according to the order of dynamics equations design corresponding ADRC. Subsequently, in consideration of the characteristics of uncertain parameter of ADRC, the Glowworm Swarm Optimization(gso) is designed to optimize the controller parameters so as to enhance the system performance. Finally, the comparative simulation for attitude of quadrotor is developed to verify the effectiveness of the proposed control strategy. The results of simulations show that the proposed controller possesses strong robustness and high performances.
The main purpose of this research is to improve the clustering accuracy of mixed attributes data. Therefore, glowworm swarm optimisation (gso) algorithm is introduced into K-prototypes algorithm to form a new clusteri...
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The main purpose of this research is to improve the clustering accuracy of mixed attributes data. Therefore, glowworm swarm optimisation (gso) algorithm is introduced into K-prototypes algorithm to form a new clustering algorithm. First, gso algorithm is improved by using the good point set. Then, the improved gso algorithm is employed to search extreme points of density in the space of data objects. The initial clustering centre of K-prototypes algorithm is chosen from the extreme points of density. Meanwhile, a unified method is designed for the distance of numeric data and categorical data. On this basis, a new clustering algorithm flow (gsoKP) is designed. Finally, the UCI datasets of numeric data, categorical data and mixed data are selected to test gsoKP algorithm. And the effectiveness of gsoKP algorithm is analysed in terms of clustering accuracy through experimental comparison.
A kind of attitude control strategy for the quadrotor based on active disturbance rejection control(ADRC) is proposed in this ***,the dynamic model using Newton–Euler formula of the quadrotor helicopter is *** accord...
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A kind of attitude control strategy for the quadrotor based on active disturbance rejection control(ADRC) is proposed in this ***,the dynamic model using Newton–Euler formula of the quadrotor helicopter is *** according to the order of dynamics equations design corresponding ***,in consideration of the characteristics of uncertain parameter of ADRC,the Glowworm Swarm Optimization(gso) is designed to optimize the controller parameters so as to enhance the system ***,the comparative simulation for attitude of quadrotor is developed to verify the effectiveness of the proposed control *** results of simulations show that the proposed controller possesses strong robustness and high performances.
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