Based on rational behavior model of three layers, a tracking control system is designed for straight line tracking which is commonly used in underwater survey missions. An intelligent PID control law implemented as pl...Based on rational behavior model of three layers, a tracking control system is designed for straight line tracking which is commonly used in underwater survey missions. An intelligent PID control law implemented as planning level during the control system using transverse deviation is came up with. Continuous tracking of path expressed by a point sequence can be realized by the law. Firstly, a path tracking control system based on rational behavior model of three layers is designed, mainly satisfying the needs of underactuated AUV. Since there is no need to perform spatially coupled maneuvers, the 3D path tracking control is decoupled into planar 2D path tracking and depth or height tracking separately. Secondly, planar path tracking controller is introduced. For the reason that more attention is paid to comparing with vertical position control, transverse deviation in analytical form is derived. According to the Lyapunov direct theory, control law is designed using discrete PID algorithm whose parameters obey adaptive fuzzy adjustment. Reference heading angle is given as an output of the guidance controller conducted by lateral deviation together with its derivative. For the purpose of improving control quality and facilitating parameter modifying, data normalize modules based on Sigmoid function are applied to input-output data manipulation. Lastly, a sequence of experiments was carried out successfully, including tests in Longfeng lake and at the Yellow sea. In most challenging sea conditions, tracking errors of straight line are below 2 m in general. The results show that AUV is able to compensate the disturbance brought by sea current. The provided test results demonstrate that the designed guidance controller guarantees stably and accurately straight route tracking. Besides, the proposed control system is accessible for continuous comb-shaped path tracking in region searching.展开更多
This paper mainly studied the problem of energy conserving in wireless sensor networks for target tracking in defensing combats. Firstly, the structures of wireless sensor nodes and networks were illustrated;Secondly,...This paper mainly studied the problem of energy conserving in wireless sensor networks for target tracking in defensing combats. Firstly, the structures of wireless sensor nodes and networks were illustrated;Secondly, the analysis of existing energy consuming in the sensing layer and its calculation method were provided to build the energy conserving objective function;What’s more, the other two indicators in target tracking, including target detection probability and tracking accuracy, were combined to be regarded as the constraints of the energy conserving objective function. Fourthly, the three energy conserving approaches, containing optimizing the management scheme, prolonging the time interval between two adjacent observations, and transmitting the observations selectively, were introduced;In addition, the improved lion algorithm combined with the Logistic chaos sequence was proposed to obtain sensor management schemes. Finally, simulations had been made to prove the effectiveness of the proposed methods and algorithm.展开更多
A fast joint probabilistic data association （FJPDA） algorithm is proposed in tiffs paper. Cluster probability matrix is approximately calculated by a new method, whose elements βi^t（K） can be taken as evaluation ...A fast joint probabilistic data association （FJPDA） algorithm is proposed in tiffs paper. Cluster probability matrix is approximately calculated by a new method, whose elements βi^t（K） can be taken as evaluation functions. According to values of βi^t（K）, N events with larger joint probabilities can be searched out as the events with guiding joint probabilities, tiros, the number of searching nodes will be greatly reduced. As a result, this method effectively reduces the calculation load and nnkes it possible to be realized on real-thne, Theoretical ,analysis and Monte Carlo simulation results show that this method is efficient.展开更多
Crowd behaviors analysis is the‘state of art’research topic in the field of computer vision which provides applications in video surveillance to crowd safety,event detection,security,etc.Literature presents some of ...Crowd behaviors analysis is the‘state of art’research topic in the field of computer vision which provides applications in video surveillance to crowd safety,event detection,security,etc.Literature presents some of the works related to crowd behavior detection and analysis.In crowd behavior detection,varying density of crowds and motion patterns appears to be complex occlusions for the researchers.This work presents a novel crowd behavior detection system to improve these restrictions.The proposed crowd behavior detection system is developed using hybrid tracking model and integrated features enabled neural network.The object movement and activity in the proposed crowded behavior detection system is assessed using proposed GSLM-based neural network.GSLM based neural network is developed by integrating the gravitational search algorithm with LM algorithm of the neural network to increase the learning process of the network.The performance of the proposed crowd behavior detection system is validated over five different videos and analyzed using accuracy.The experimentation results in the crowd behavior detection with a maximum accuracy of 93%which proves the efficacy of the proposed system in video surveillance with security concerns.展开更多
In this paper, we propose multiple CAMShift Algorithm based on Kalman filter and weighted search windows that extracts skin color area and tracks several human body parts for real-time human tracking system. The CAMSh...In this paper, we propose multiple CAMShift Algorithm based on Kalman filter and weighted search windows that extracts skin color area and tracks several human body parts for real-time human tracking system. The CAMShift Algorithm we propose searches the skin color region by detecting the skin color area from background model. Kalman filter stabilizes the floated search area of CAMShift Algorithm. Each occlusion areas are avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed modified Camshaft algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.展开更多
The development of welding robots suitable for specially unstructured working enviroments has been become an important development direction of industrial robot application because large-scale welding structures have ...The development of welding robots suitable for specially unstructured working enviroments has been become an important development direction of industrial robot application because large-scale welding structures have been used more and more widely in modern industry. In this paper, an intelligent mobile robot for welding of ship deck with the function of autosearching weld line was presented. A wheeled motion mechanism and a cross adjustment slider are used for the welding robot body. A sensing system based on laser-PSD （position sensitive detector） displacement sensor was developed to obtain two dimensional deviation signals during seam tracking. A full-digital control system based on DSP and CPLD has also been realized to implement complex and high-performance control algorithms. Furthermore, the system has still the function of auto-searching weld line according to the characteristics information of weld groove and adjusting posture itself to the desired status preparing for welding. The experiment of auto-searching welding line shows that the robot has high tracing accuracy, and can satisfy the requirement of practical welding project.展开更多
光伏阵列P-U特性曲线在局部遮阴状态下呈现多峰状态,传统的最大功率追踪算法容易陷入局部最优状态。针对此问题,提出了一种基于改进麻雀搜索算法的最大功率点跟踪(maximum power point tracking,MPPT)方法。在麻雀搜索算法中引入遗传算...光伏阵列P-U特性曲线在局部遮阴状态下呈现多峰状态,传统的最大功率追踪算法容易陷入局部最优状态。针对此问题,提出了一种基于改进麻雀搜索算法的最大功率点跟踪(maximum power point tracking,MPPT)方法。在麻雀搜索算法中引入遗传算法和Lévy飞行策略,使算法的全局搜索能力得以增强,并且可以跳出局部最优解。在MATLAB/Simulink中建立仿真模型,并与粒子群优化算法和原始麻雀搜索算法进行比较。仿真结果表明,基于改进麻雀搜索算法的MPPT方法在不同光照条件下均显示出更高的效率和稳定性。展开更多
针对光照强度不均匀造成光伏阵列的输出曲线为多峰曲线,传统最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制算法不能跟踪到全局最大功率的问题,文章提出一种基于改进麻雀搜索算法(Improved the Sparrow Search Algorithm,ISSA...针对光照强度不均匀造成光伏阵列的输出曲线为多峰曲线,传统最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制算法不能跟踪到全局最大功率的问题,文章提出一种基于改进麻雀搜索算法(Improved the Sparrow Search Algorithm,ISSA)和扰动观察法(Perturbation and Observation Method,P&O)的光储发电系统MPPT控制方法。首先,在跟踪前期,采用混沌映射方式增加ISSA种群多样性,提升算法广泛搜索能力。为了防止算法陷入局部最优,利用萤火虫扰动算法对麻雀个体进行扰动更新;其次,在跟踪后期,使用P&O防止系统在最大功率点附近振荡,保证最大功率点稳定输出;最后,经过算例分析,所提MPPT控制方法实现了不同场景下的快速跟踪、精准输出,能够很好应用地于光储混合发电系统中。展开更多
The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo searc...The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo search algorithm. In order to enhance the search capability of the cuckoo search algorithm, the adaptive detection probability and amplification factor are designed. Finally, the control allocation method based on the proposed improved cuckoo search algorithm is applied to the tracking control problem of the innovative control effector aircraft. The comparative simulation results demonstrate the superiority and effectiveness of the proposed improved cuckoo search algorithm in control allocation of aircraft.展开更多
The existing Maximum Power Point Tracking(MPPT)method has low tracking efficiency and poor stability.It is easy to fall into the Local Maximum Power Point(LMPP)in Partial Shading Condition(PSC),resulting in the degrad...The existing Maximum Power Point Tracking(MPPT)method has low tracking efficiency and poor stability.It is easy to fall into the Local Maximum Power Point(LMPP)in Partial Shading Condition(PSC),resulting in the degradation of output power quality and efficiency.It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms,and their performance in tracking the Global Maximum Power Point(GMPP)varies.Thus,a Cuckoo search algorithm(CSA)combined with the Incremental conductance Algorithm(INC)is proposed(CSA-INC)is put forward for the MPPT method of photovoltaic power generation.The method can improve the tracking speed by more than 52%compared with the traditional Cuckoo Search Algorithm(CSA),and the results of the study using this algorithm are compared with the popular Particle Swarm Optimization(PSO)and the Gravitational Search Algorithm(GSA).CSA-INC has an average tracking efficiency of 99.99%and an average tracking time of 0.19 s when tracking the GMPP,which improves PV power generation’s efficiency and power quality.展开更多
For the past few years,wind energy is the most popular non-traditional resource among renewable energy resources and it’s significant to make full use of wind energy to realize a high level of generating power.Moreov...For the past few years,wind energy is the most popular non-traditional resource among renewable energy resources and it’s significant to make full use of wind energy to realize a high level of generating power.Moreover,diverse maximum power point tracking(MPPT)methods have been designed for varying speed operation of wind energy conversion system(WECS)applications to obtain optimal power extraction.Hence,a novel and metaheuristic technique,named enhanced atom search optimization(EASO),is designed for a permanent magnet synchronous generator(PMSG)based WECS,which can be employed to track the maximum power point.One of the most promising benefits of this technique is powerful global search capability that leads to fast response and high-quality optimal solution.Besides,in contrast with other conventional meta-heuristic techniques,EASO is extremely not relying on the original solution,which can avoid sinking into a low-quality local maximum power point(LMPP)by realizing an appropriate trade-off between global exploration and local exploitation.At last,simulations employing two case studies through Matlab/Simulink validate the practicability and effectiveness of the proposed techniques for optimal proportional-integral-derivative(PID)control parameters tuning of PMSG based WECS under a variety of wind conditions.展开更多
光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该...光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该文提出了一种基于麻雀搜索算法优化的极限学习机(sparrow search algorithm-extreme learning machine,SSA-ELM)神经网络控制器的MPPT方法。与传统技术相比,该MPPT方法在稳定性、速度、超调和MPP的振荡等方面的效果均较好。使用MATLAB/Simulink平台进行仿真实验,验证了所提控制策略及理论分析的正确性。展开更多
基金Projects(51179035,51279221) supported by the National Natural Science Foundation of ChinaProject(2014M561333) supported by Postdoctoral Science Foundation of China
文摘Based on rational behavior model of three layers, a tracking control system is designed for straight line tracking which is commonly used in underwater survey missions. An intelligent PID control law implemented as planning level during the control system using transverse deviation is came up with. Continuous tracking of path expressed by a point sequence can be realized by the law. Firstly, a path tracking control system based on rational behavior model of three layers is designed, mainly satisfying the needs of underactuated AUV. Since there is no need to perform spatially coupled maneuvers, the 3D path tracking control is decoupled into planar 2D path tracking and depth or height tracking separately. Secondly, planar path tracking controller is introduced. For the reason that more attention is paid to comparing with vertical position control, transverse deviation in analytical form is derived. According to the Lyapunov direct theory, control law is designed using discrete PID algorithm whose parameters obey adaptive fuzzy adjustment. Reference heading angle is given as an output of the guidance controller conducted by lateral deviation together with its derivative. For the purpose of improving control quality and facilitating parameter modifying, data normalize modules based on Sigmoid function are applied to input-output data manipulation. Lastly, a sequence of experiments was carried out successfully, including tests in Longfeng lake and at the Yellow sea. In most challenging sea conditions, tracking errors of straight line are below 2 m in general. The results show that AUV is able to compensate the disturbance brought by sea current. The provided test results demonstrate that the designed guidance controller guarantees stably and accurately straight route tracking. Besides, the proposed control system is accessible for continuous comb-shaped path tracking in region searching.
基金funded by (Defense Pre-Research Fund Project of China), grant number 012015012600A2203NSFC (Natural Science Foundation of China), grant number 61573374。
文摘This paper mainly studied the problem of energy conserving in wireless sensor networks for target tracking in defensing combats. Firstly, the structures of wireless sensor nodes and networks were illustrated;Secondly, the analysis of existing energy consuming in the sensing layer and its calculation method were provided to build the energy conserving objective function;What’s more, the other two indicators in target tracking, including target detection probability and tracking accuracy, were combined to be regarded as the constraints of the energy conserving objective function. Fourthly, the three energy conserving approaches, containing optimizing the management scheme, prolonging the time interval between two adjacent observations, and transmitting the observations selectively, were introduced;In addition, the improved lion algorithm combined with the Logistic chaos sequence was proposed to obtain sensor management schemes. Finally, simulations had been made to prove the effectiveness of the proposed methods and algorithm.
文摘A fast joint probabilistic data association （FJPDA） algorithm is proposed in tiffs paper. Cluster probability matrix is approximately calculated by a new method, whose elements βi^t（K） can be taken as evaluation functions. According to values of βi^t（K）, N events with larger joint probabilities can be searched out as the events with guiding joint probabilities, tiros, the number of searching nodes will be greatly reduced. As a result, this method effectively reduces the calculation load and nnkes it possible to be realized on real-thne, Theoretical ,analysis and Monte Carlo simulation results show that this method is efficient.
文摘Crowd behaviors analysis is the‘state of art’research topic in the field of computer vision which provides applications in video surveillance to crowd safety,event detection,security,etc.Literature presents some of the works related to crowd behavior detection and analysis.In crowd behavior detection,varying density of crowds and motion patterns appears to be complex occlusions for the researchers.This work presents a novel crowd behavior detection system to improve these restrictions.The proposed crowd behavior detection system is developed using hybrid tracking model and integrated features enabled neural network.The object movement and activity in the proposed crowded behavior detection system is assessed using proposed GSLM-based neural network.GSLM based neural network is developed by integrating the gravitational search algorithm with LM algorithm of the neural network to increase the learning process of the network.The performance of the proposed crowd behavior detection system is validated over five different videos and analyzed using accuracy.The experimentation results in the crowd behavior detection with a maximum accuracy of 93%which proves the efficacy of the proposed system in video surveillance with security concerns.
文摘In this paper, we propose multiple CAMShift Algorithm based on Kalman filter and weighted search windows that extracts skin color area and tracks several human body parts for real-time human tracking system. The CAMShift Algorithm we propose searches the skin color region by detecting the skin color area from background model. Kalman filter stabilizes the floated search area of CAMShift Algorithm. Each occlusion areas are avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed modified Camshaft algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.
文摘The development of welding robots suitable for specially unstructured working enviroments has been become an important development direction of industrial robot application because large-scale welding structures have been used more and more widely in modern industry. In this paper, an intelligent mobile robot for welding of ship deck with the function of autosearching weld line was presented. A wheeled motion mechanism and a cross adjustment slider are used for the welding robot body. A sensing system based on laser-PSD （position sensitive detector） displacement sensor was developed to obtain two dimensional deviation signals during seam tracking. A full-digital control system based on DSP and CPLD has also been realized to implement complex and high-performance control algorithms. Furthermore, the system has still the function of auto-searching weld line according to the characteristics information of weld groove and adjusting posture itself to the desired status preparing for welding. The experiment of auto-searching welding line shows that the robot has high tracing accuracy, and can satisfy the requirement of practical welding project.
文摘光伏阵列P-U特性曲线在局部遮阴状态下呈现多峰状态,传统的最大功率追踪算法容易陷入局部最优状态。针对此问题,提出了一种基于改进麻雀搜索算法的最大功率点跟踪(maximum power point tracking,MPPT)方法。在麻雀搜索算法中引入遗传算法和Lévy飞行策略,使算法的全局搜索能力得以增强,并且可以跳出局部最优解。在MATLAB/Simulink中建立仿真模型,并与粒子群优化算法和原始麻雀搜索算法进行比较。仿真结果表明,基于改进麻雀搜索算法的MPPT方法在不同光照条件下均显示出更高的效率和稳定性。
文摘针对光照强度不均匀造成光伏阵列的输出曲线为多峰曲线,传统最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制算法不能跟踪到全局最大功率的问题,文章提出一种基于改进麻雀搜索算法(Improved the Sparrow Search Algorithm,ISSA)和扰动观察法(Perturbation and Observation Method,P&O)的光储发电系统MPPT控制方法。首先,在跟踪前期,采用混沌映射方式增加ISSA种群多样性,提升算法广泛搜索能力。为了防止算法陷入局部最优,利用萤火虫扰动算法对麻雀个体进行扰动更新;其次,在跟踪后期,使用P&O防止系统在最大功率点附近振荡,保证最大功率点稳定输出;最后,经过算例分析,所提MPPT控制方法实现了不同场景下的快速跟踪、精准输出,能够很好应用地于光储混合发电系统中。
基金supported by the National Natural Science Foundation of China(61273083 and 61374012)
文摘The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo search algorithm. In order to enhance the search capability of the cuckoo search algorithm, the adaptive detection probability and amplification factor are designed. Finally, the control allocation method based on the proposed improved cuckoo search algorithm is applied to the tracking control problem of the innovative control effector aircraft. The comparative simulation results demonstrate the superiority and effectiveness of the proposed improved cuckoo search algorithm in control allocation of aircraft.
基金supported by the Natural Science Foundation of Gansu Province(Grant No.21JR7RA321)。
文摘The existing Maximum Power Point Tracking(MPPT)method has low tracking efficiency and poor stability.It is easy to fall into the Local Maximum Power Point(LMPP)in Partial Shading Condition(PSC),resulting in the degradation of output power quality and efficiency.It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms,and their performance in tracking the Global Maximum Power Point(GMPP)varies.Thus,a Cuckoo search algorithm(CSA)combined with the Incremental conductance Algorithm(INC)is proposed(CSA-INC)is put forward for the MPPT method of photovoltaic power generation.The method can improve the tracking speed by more than 52%compared with the traditional Cuckoo Search Algorithm(CSA),and the results of the study using this algorithm are compared with the popular Particle Swarm Optimization(PSO)and the Gravitational Search Algorithm(GSA).CSA-INC has an average tracking efficiency of 99.99%and an average tracking time of 0.19 s when tracking the GMPP,which improves PV power generation’s efficiency and power quality.
基金The authors appreciatively acknowledge the support of rapid device state variation based system device invention of a training device for live-work electricity meter installation without electric shocks(YNZC202003110011)National Natural Science Foundation of China(NSFC)under Grant(61902039).
文摘For the past few years,wind energy is the most popular non-traditional resource among renewable energy resources and it’s significant to make full use of wind energy to realize a high level of generating power.Moreover,diverse maximum power point tracking(MPPT)methods have been designed for varying speed operation of wind energy conversion system(WECS)applications to obtain optimal power extraction.Hence,a novel and metaheuristic technique,named enhanced atom search optimization(EASO),is designed for a permanent magnet synchronous generator(PMSG)based WECS,which can be employed to track the maximum power point.One of the most promising benefits of this technique is powerful global search capability that leads to fast response and high-quality optimal solution.Besides,in contrast with other conventional meta-heuristic techniques,EASO is extremely not relying on the original solution,which can avoid sinking into a low-quality local maximum power point(LMPP)by realizing an appropriate trade-off between global exploration and local exploitation.At last,simulations employing two case studies through Matlab/Simulink validate the practicability and effectiveness of the proposed techniques for optimal proportional-integral-derivative(PID)control parameters tuning of PMSG based WECS under a variety of wind conditions.
文摘光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该文提出了一种基于麻雀搜索算法优化的极限学习机(sparrow search algorithm-extreme learning machine,SSA-ELM)神经网络控制器的MPPT方法。与传统技术相比,该MPPT方法在稳定性、速度、超调和MPP的振荡等方面的效果均较好。使用MATLAB/Simulink平台进行仿真实验,验证了所提控制策略及理论分析的正确性。
