The Wireless Sensor Network(WSN)is a network that is constructed in regions that are inaccessible to human beings.The widespread deployment of wireless micro sensors will make it possible to conduct accurate environme...The Wireless Sensor Network(WSN)is a network that is constructed in regions that are inaccessible to human beings.The widespread deployment of wireless micro sensors will make it possible to conduct accurate environmental monitoring for a use in both civil and military environments.They make use of these data to monitor and keep track of the physical data of the surrounding environment in order to ensure the sustainability of the area.The data have to be picked up by the sensor,and then sent to the sink node where they may be processed.The nodes of the WSNs are powered by batteries,therefore they eventually run out of power.This energy restriction has an effect on the network life span and environmental sustainability.The objective of this study is to further improve the Engroove Leach(EL)protocol’s energy efficiency so that the network can operate for a very long time while consuming the least amount of energy.The lifespan of WSNs is being extended often using clustering and routing strategies.The Meta Inspired Hawks Fragment Optimization(MIHFO)system,which is based on passive clustering,is used in this study to do clustering.The cluster head is chosen based on the nodes’residual energy,distance to neighbors,distance to base station,node degree,and node centrality.Based on distance,residual energy,and node degree,an algorithm known as Heuristic Wing Antfly Optimization(HWAFO)selects the optimum path between the cluster head and Base Station(BS).They examine the number of nodes that are active,their energy consumption,and the number of data packets that the BS receives.The overall experimentation is carried out under the MATLAB environment.From the analysis,it has been discovered that the suggested approach yields noticeably superior outcomes in terms of throughput,packet delivery and drop ratio,and average energy consumption.展开更多
A new bionic approach is presented to find the optimal topologies of a structure with tension-only or compression-onlymaterial based on bone remodelling theory.By traditional methods,the computational cost of topology...A new bionic approach is presented to find the optimal topologies of a structure with tension-only or compression-onlymaterial based on bone remodelling theory.By traditional methods,the computational cost of topology optimization of thestructure is high due to material nonlinearity.To improve the efficiency of optimization,the reference-interval with material-replacement method is presented.In the method,firstly,the optimization process of a structure is considered as bone remodellingprocess under the same loading conditions.A reference interval of Strain Energy Density (SED),corresponding to thedead zone or lazy zone in bone mechanics,is adopted to control the update of the design variables.Secondly,a material-replacement scheme is used to simplify the Finite Element Analysis (FEA) of structure in optimization.In the operation ofmaterial-replacement,the original tension-only or compression-only material in design domain is replaced with a new isotropicmaterial and the Effective Strain Energy Density (ESED) of each element can be obtained.Finally,the update of design variablesis determined by comparing the local ESED and the current reference interval of SED,e.g.,the increment of a relativedensity is nonzero if the local ESED is out of the current reference interval.Numerical results validate the method.展开更多
Multi-objective data clustering is an important issue in data mining, and the realization of data clustering using the multiobjective optimization technique is a significant topic. A combinatorial multi-objective pige...Multi-objective data clustering is an important issue in data mining, and the realization of data clustering using the multiobjective optimization technique is a significant topic. A combinatorial multi-objective pigeon inspired optimization(CMOPIO)with ring topology is proposed to solve the clustering problem in this paper. In the CMOPIO, a delta-locus based coding approach is employed to encode the pigeons. Thus, the length of pigeon representation and the dimension of the search space are significantly reduced. Thereby, the computational load can be effectively depressed. In this way, the pigeon inspired optimization(PIO) algorithm can be discretized with an auxiliary vector to address data clustering. Moreover, an index-based ring topology with the ability of contributing to maintain flock diversity is adopted to improve the CMOPIO performance. Comparative simulation results demonstrate the feasibility and effectiveness of our proposed CMOPIO for solving data clustering problems.展开更多
In this article, the formation control of quad-rotor unmanned aerial vehicle(UAV) via pigeon inspired optimization(PIO) is designed. The nonlinear mathematical model of the quad-rotor UAV is used by applying algebraic...In this article, the formation control of quad-rotor unmanned aerial vehicle(UAV) via pigeon inspired optimization(PIO) is designed. The nonlinear mathematical model of the quad-rotor UAV is used by applying algebraic graph theory and matrix analysis. A high order consistent formation control algorithm with fixed control topology is designed by using a position deviation matrix to describe its formation. To control the attitude of quad-rotor UAVs, it is difficult to obtain a set of optimal solutions, and hence a PIO based algorithm with variable weight hybridization is proposed. The algorithm is mainly composed of two parts. First, according to the distance between the particles in the iterative process, the inertia weight is dynamically changed,and the coefficient is adjusted to control the degree of influence on its inertia weight. Second, the overall scenario is designed by using MATLAB based simulations which show that the formation control of the quad-rotor UAV is achieved with the help of PIO.展开更多
We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy fli...We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy flight based pigeon inspired optimization(LFPIO).First,we propose a non-singular fast terminal sliding mode observer(NFTSMO)to estimate the influence of a disturbance,and prove that the observer converges in fixed time using a Lyapunov function.Second,we design an obstacle avoidance strategy based on topology reconstruction,by which the UAV can save energy and safely pass obstacles.Third,we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors.Further,the cost function of each UAV is designed,by which the UAV formation problem is transformed into a game problem.Finally,we develop LFPIO and use it to solve the Nash equilibrium.Numerical simulations are conducted,and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.展开更多
基金supported via funding from Prince Sattam Bin Abdulaziz University(No.PSAU/2023/R/1444).
文摘The Wireless Sensor Network(WSN)is a network that is constructed in regions that are inaccessible to human beings.The widespread deployment of wireless micro sensors will make it possible to conduct accurate environmental monitoring for a use in both civil and military environments.They make use of these data to monitor and keep track of the physical data of the surrounding environment in order to ensure the sustainability of the area.The data have to be picked up by the sensor,and then sent to the sink node where they may be processed.The nodes of the WSNs are powered by batteries,therefore they eventually run out of power.This energy restriction has an effect on the network life span and environmental sustainability.The objective of this study is to further improve the Engroove Leach(EL)protocol’s energy efficiency so that the network can operate for a very long time while consuming the least amount of energy.The lifespan of WSNs is being extended often using clustering and routing strategies.The Meta Inspired Hawks Fragment Optimization(MIHFO)system,which is based on passive clustering,is used in this study to do clustering.The cluster head is chosen based on the nodes’residual energy,distance to neighbors,distance to base station,node degree,and node centrality.Based on distance,residual energy,and node degree,an algorithm known as Heuristic Wing Antfly Optimization(HWAFO)selects the optimum path between the cluster head and Base Station(BS).They examine the number of nodes that are active,their energy consumption,and the number of data packets that the BS receives.The overall experimentation is carried out under the MATLAB environment.From the analysis,it has been discovered that the suggested approach yields noticeably superior outcomes in terms of throughput,packet delivery and drop ratio,and average energy consumption.
基金the National Natural Science Foundation of China(Grant No.50908190)the Human Resources Foundation of Northwest A&F University(Grant No.Z111020903)
文摘A new bionic approach is presented to find the optimal topologies of a structure with tension-only or compression-onlymaterial based on bone remodelling theory.By traditional methods,the computational cost of topology optimization of thestructure is high due to material nonlinearity.To improve the efficiency of optimization,the reference-interval with material-replacement method is presented.In the method,firstly,the optimization process of a structure is considered as bone remodellingprocess under the same loading conditions.A reference interval of Strain Energy Density (SED),corresponding to thedead zone or lazy zone in bone mechanics,is adopted to control the update of the design variables.Secondly,a material-replacement scheme is used to simplify the Finite Element Analysis (FEA) of structure in optimization.In the operation ofmaterial-replacement,the original tension-only or compression-only material in design domain is replaced with a new isotropicmaterial and the Effective Strain Energy Density (ESED) of each element can be obtained.Finally,the update of design variablesis determined by comparing the local ESED and the current reference interval of SED,e.g.,the increment of a relativedensity is nonzero if the local ESED is out of the current reference interval.Numerical results validate the method.
基金supported by the Science and Technology Innovation 2030-Key Project of “New Generation Artificial Intelligence”(Grant No.2018AAA0102303)the National Natural Science Foundation of China(Grant Nos. 91948204,U1913602.and U19B2033)。
文摘Multi-objective data clustering is an important issue in data mining, and the realization of data clustering using the multiobjective optimization technique is a significant topic. A combinatorial multi-objective pigeon inspired optimization(CMOPIO)with ring topology is proposed to solve the clustering problem in this paper. In the CMOPIO, a delta-locus based coding approach is employed to encode the pigeons. Thus, the length of pigeon representation and the dimension of the search space are significantly reduced. Thereby, the computational load can be effectively depressed. In this way, the pigeon inspired optimization(PIO) algorithm can be discretized with an auxiliary vector to address data clustering. Moreover, an index-based ring topology with the ability of contributing to maintain flock diversity is adopted to improve the CMOPIO performance. Comparative simulation results demonstrate the feasibility and effectiveness of our proposed CMOPIO for solving data clustering problems.
文摘In this article, the formation control of quad-rotor unmanned aerial vehicle(UAV) via pigeon inspired optimization(PIO) is designed. The nonlinear mathematical model of the quad-rotor UAV is used by applying algebraic graph theory and matrix analysis. A high order consistent formation control algorithm with fixed control topology is designed by using a position deviation matrix to describe its formation. To control the attitude of quad-rotor UAVs, it is difficult to obtain a set of optimal solutions, and hence a PIO based algorithm with variable weight hybridization is proposed. The algorithm is mainly composed of two parts. First, according to the distance between the particles in the iterative process, the inertia weight is dynamically changed,and the coefficient is adjusted to control the degree of influence on its inertia weight. Second, the overall scenario is designed by using MATLAB based simulations which show that the formation control of the quad-rotor UAV is achieved with the help of PIO.
基金Project supported by the Science and Technology Innovation 2030 Key Project of“New Generation Artificial Intelligence,”China(No.2018AAA0100803)the National Natural Science Foundation of China(Nos.T2121003,U1913602,U20B2071,91948204,and U19B2033)。
文摘We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy flight based pigeon inspired optimization(LFPIO).First,we propose a non-singular fast terminal sliding mode observer(NFTSMO)to estimate the influence of a disturbance,and prove that the observer converges in fixed time using a Lyapunov function.Second,we design an obstacle avoidance strategy based on topology reconstruction,by which the UAV can save energy and safely pass obstacles.Third,we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors.Further,the cost function of each UAV is designed,by which the UAV formation problem is transformed into a game problem.Finally,we develop LFPIO and use it to solve the Nash equilibrium.Numerical simulations are conducted,and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.
