Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the ...Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.展开更多
Relocation is an important event in the lives of several social insects whereby all colony members have to be transferred to a new nest when conditions in the old nest become unfavorable. In the current study, network...Relocation is an important event in the lives of several social insects whereby all colony members have to be transferred to a new nest when conditions in the old nest become unfavorable. In the current study, network tools were used to examine the organization of this goal-oriented task in the Indian queenless ant Diacamma indicum Which relocate their colonies by means of tandem running. Individual ants were used as nodes and tandem runs as directed edges to construct unweighted networks. Network parameters were characterized in control relocations （CRs） and in relocations where the node with the highest outdegree, that is, the Maximum tandem leader （Max TL） was experimentally removed. These were then compared to 1） randomized networks, 2） simu- lated networks in which Max TL was removed, and 3） simulated networks with removal of a random leader. Not only was there complete recovery of the task, but the manner in which it was organized when Max TL was removed was comparable to CRs. The results obtained from our empirical study were significantly different from the results predicted by simulations of leader removal. At an individual level, the Max TL had a significantly higher outdegree than expected by chance alone and in her absence the substitute Max TL did comparable work. In addition, the position of the Max TL in the pathway of information flow was conserved in control and experimentally manipulated conditions. Understanding the organization of this critical event as more than the sum of individual interactions using network parameters allows us to appreciate the dynamic response of groups to perturbations.展开更多
基金authorities of East Tehran Branch,Islamic Azad University,Tehran,Iran,for providing support and necessary facilities
文摘Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.
文摘Relocation is an important event in the lives of several social insects whereby all colony members have to be transferred to a new nest when conditions in the old nest become unfavorable. In the current study, network tools were used to examine the organization of this goal-oriented task in the Indian queenless ant Diacamma indicum Which relocate their colonies by means of tandem running. Individual ants were used as nodes and tandem runs as directed edges to construct unweighted networks. Network parameters were characterized in control relocations （CRs） and in relocations where the node with the highest outdegree, that is, the Maximum tandem leader （Max TL） was experimentally removed. These were then compared to 1） randomized networks, 2） simu- lated networks in which Max TL was removed, and 3） simulated networks with removal of a random leader. Not only was there complete recovery of the task, but the manner in which it was organized when Max TL was removed was comparable to CRs. The results obtained from our empirical study were significantly different from the results predicted by simulations of leader removal. At an individual level, the Max TL had a significantly higher outdegree than expected by chance alone and in her absence the substitute Max TL did comparable work. In addition, the position of the Max TL in the pathway of information flow was conserved in control and experimentally manipulated conditions. Understanding the organization of this critical event as more than the sum of individual interactions using network parameters allows us to appreciate the dynamic response of groups to perturbations.
