This article presents a new two-axis solar tracker based on an online optimization algorithm so as to track the position of the sun without using its movement model.In this research,four well-known optimization algori...This article presents a new two-axis solar tracker based on an online optimization algorithm so as to track the position of the sun without using its movement model.In this research,four well-known optimization algorithms are employed to find the two unknown parameters named azimuth and zenith angles,which determine the position of the sun.The magnitude of the sunray is considered as the cost function of all algorithms.Then,several experiments are carried out to find the best optimization algorithm with optimal population size,number of iterations,and also the best initialization method.Uniform initialization leads to faster convergence compared to random initialization.The results clearly show that the particle swarm optimization algorithm with a population size of 15 and 7 iterations using uniform initialization method has better performance than the other algorithms,with a convergence time of less than 40 s.The average fitness value or voltage received by the tracker is 2.4 Volts in this method,which is higher than other methods.TLBO also performs well with a population size of 15 and 7 iterations.Afterward,the artificial neural network with one hidden layer and 20 neurons is employed to predict these two parameters in each day and moment in a year in Shiraz city according to the experimental data extracted from PSO.Number of the day from January and the time are inputs and zenith and azimuth angles are considered the output of neural network modeling.The performance of the proposed ANN model is evaluated using regression plots,demonstrating a strong correlation between predicted and target outputs.Finally,the outcomes reveal the feasibility of using online optimization algorithms and neural network modeling in an effort to bypass the complex mathematical model of mechatronic systems and predict the movement of the sun automatically.展开更多
Two-axis transportable satellite antennas(TATSAs) have been widely adopted owing to its simple structure and low cost. However, by searching in a wide range, it will take a very long searching time. Under extreme cond...Two-axis transportable satellite antennas(TATSAs) have been widely adopted owing to its simple structure and low cost. However, by searching in a wide range, it will take a very long searching time. Under extreme conditions, it will even fail to work. In this paper, we propose a novel roll compensation(RC) method for the low-cost TATSAs to achieve faster tracking even if when the antenna has no azimuth sensor. By analyzing the influence of roll axis on the system performance, details of the compensation method are derived. Simulation and measurement results indicate that the proposed RC method can effectively reduce the initial searching time for satellite communication. In addition, tracking along with the ellipse path with the RC method provides the highest tracking efficiency.展开更多
Multi-mode cavities have now attracted much attention both experimentally and theoretically. In this paper, inspired by recent experiments of cavity-assisted Raman transitions, we realize a two-axis spin Hamiltonian H...Multi-mode cavities have now attracted much attention both experimentally and theoretically. In this paper, inspired by recent experiments of cavity-assisted Raman transitions, we realize a two-axis spin Hamiltonian H = q（J_x^2＋ χJ_y^2） ＋ ω_0J_z in two cavities. This realized Hamiltonian has a distinct property that all parameters can be tuned independently. For proper parameters, the well-studied one- and two-axis twisting Hamiltonians are recovered, and the scaling of N^（-1） of the maximal squeezing factor can occur naturally. On the other hand, in the two-axis twisting Hamiltonian, spin squeezing is usually reduced when increasing the atomic resonant frequency ω_0. Surprisingly, we find that by combining with the dimensionless parameter χ（-1）, this atomic resonant frequency ω_0 can enhance spin squeezing greatly. These results are beneficial for achieving the required spin squeezing in experiments.展开更多
The theory and algorithm of Singular Value Decomposition(SVD) is introduced.The advantage of Singular Value Decomposition used in system identification is studied,compared and illustrated through analyzing the data of...The theory and algorithm of Singular Value Decomposition(SVD) is introduced.The advantage of Singular Value Decomposition used in system identification is studied,compared and illustrated through analyzing the data of navigational gyroscopes drift in two-axis servo testing.展开更多
文摘This article presents a new two-axis solar tracker based on an online optimization algorithm so as to track the position of the sun without using its movement model.In this research,four well-known optimization algorithms are employed to find the two unknown parameters named azimuth and zenith angles,which determine the position of the sun.The magnitude of the sunray is considered as the cost function of all algorithms.Then,several experiments are carried out to find the best optimization algorithm with optimal population size,number of iterations,and also the best initialization method.Uniform initialization leads to faster convergence compared to random initialization.The results clearly show that the particle swarm optimization algorithm with a population size of 15 and 7 iterations using uniform initialization method has better performance than the other algorithms,with a convergence time of less than 40 s.The average fitness value or voltage received by the tracker is 2.4 Volts in this method,which is higher than other methods.TLBO also performs well with a population size of 15 and 7 iterations.Afterward,the artificial neural network with one hidden layer and 20 neurons is employed to predict these two parameters in each day and moment in a year in Shiraz city according to the experimental data extracted from PSO.Number of the day from January and the time are inputs and zenith and azimuth angles are considered the output of neural network modeling.The performance of the proposed ANN model is evaluated using regression plots,demonstrating a strong correlation between predicted and target outputs.Finally,the outcomes reveal the feasibility of using online optimization algorithms and neural network modeling in an effort to bypass the complex mathematical model of mechatronic systems and predict the movement of the sun automatically.
基金jointly sponsored by scientific research foundation NUPTSF(Grant No.NY-214144 and Grant No.NY-215073)NSFC(Grant No.61701260)
文摘Two-axis transportable satellite antennas(TATSAs) have been widely adopted owing to its simple structure and low cost. However, by searching in a wide range, it will take a very long searching time. Under extreme conditions, it will even fail to work. In this paper, we propose a novel roll compensation(RC) method for the low-cost TATSAs to achieve faster tracking even if when the antenna has no azimuth sensor. By analyzing the influence of roll axis on the system performance, details of the compensation method are derived. Simulation and measurement results indicate that the proposed RC method can effectively reduce the initial searching time for satellite communication. In addition, tracking along with the ellipse path with the RC method provides the highest tracking efficiency.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11422433,11447028,61227902,11434007,and 61275211)the Natural Science Foundation of Zhejiang Province,China(Grant No.LY13A040001)the Scientific Research Foundation of the Education Department of Zhejiang Province,China(Grant No.Y201122352)
文摘Multi-mode cavities have now attracted much attention both experimentally and theoretically. In this paper, inspired by recent experiments of cavity-assisted Raman transitions, we realize a two-axis spin Hamiltonian H = q（J_x^2＋ χJ_y^2） ＋ ω_0J_z in two cavities. This realized Hamiltonian has a distinct property that all parameters can be tuned independently. For proper parameters, the well-studied one- and two-axis twisting Hamiltonians are recovered, and the scaling of N^（-1） of the maximal squeezing factor can occur naturally. On the other hand, in the two-axis twisting Hamiltonian, spin squeezing is usually reduced when increasing the atomic resonant frequency ω_0. Surprisingly, we find that by combining with the dimensionless parameter χ（-1）, this atomic resonant frequency ω_0 can enhance spin squeezing greatly. These results are beneficial for achieving the required spin squeezing in experiments.
文摘The theory and algorithm of Singular Value Decomposition(SVD) is introduced.The advantage of Singular Value Decomposition used in system identification is studied,compared and illustrated through analyzing the data of navigational gyroscopes drift in two-axis servo testing.
