In this paper, a class of generalized strongly nonlinear quasivariational inclusions are studied. By using the properties of the resolvent operator associated with a maximal monotone; mapping in Hilbert space, an exis...In this paper, a class of generalized strongly nonlinear quasivariational inclusions are studied. By using the properties of the resolvent operator associated with a maximal monotone; mapping in Hilbert space, an existence theorem of solutions for generalized strongly nonlinear quasivariational inclusion is established and a new proximal point algorithm with errors is suggested for finding approximate solutions which strongly converge to the exact solution of the generalized strongly, nonlinear quasivariational inclusion. As special cases, some known results in this field are also discussed.展开更多
The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location ...The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location performance of the time sum of arrival(TSOA) algorithm from the root mean square error(RMSE) and geometric dilution of precision(GDOP) in additive white Gaussian noise(AWGN) environment. The TSOA localization model is constructed. Using it, the distribution of location ambiguity region is presented with 4-base stations. And then, the location performance analysis is started from the 4-base stations with calculating the RMSE and GDOP variation. Subsequently, when the location parameters are changed in number of base stations, base station layout and so on, the performance changing patterns of the TSOA location algorithm are shown. So, the TSOA location characteristics and performance are revealed. From the RMSE and GDOP state changing trend, the anti-noise performance and robustness of the TSOA localization algorithm are proved. The TSOA anti-noise performance will be used for reducing the blind-zone and the false location rate of MLAT systems.展开更多
According to the test data of subdivision errors in the measuring cycle of angular measuring system, the characteristics of subdivision errors generated by this system are analyzed. It is found that the subdivision er...According to the test data of subdivision errors in the measuring cycle of angular measuring system, the characteristics of subdivision errors generated by this system are analyzed. It is found that the subdivision errors are mainly due to the rotary-type inductosyn itself. For the characteristic of cyclical change, the subdivision errors in other measuring cycles can be compensated by the subdivision error model in one measuring cycle. Using the measured error data as training samples, combining GA and BP algorithm, an ANN model of subdivision error is designed. Simulation results indicate that GA reduces the uncertainty in the training process of the ANN model, and enhances the generalization of the model. Compared with the error model based on the least-mean-squared method, the designed ANN model of subdivision errors can achieve higher compensating precision.展开更多
A genetic algorithm(GA)-based new method is designed to evaluate thecircularity error of mechanical parts. The method uses the capability of nonlinear optimization ofGA to search for the optimal solution of circularit...A genetic algorithm(GA)-based new method is designed to evaluate thecircularity error of mechanical parts. The method uses the capability of nonlinear optimization ofGA to search for the optimal solution of circularity error. The finely-designed GA (FDGA)characterized dynamical bisexual recombination and Gaussian mutation. The mathematical model of thenonlinear problem is given. The implementation details in FDGA are described such as the crossoveror recombination mechanism which utilized a bisexual reproduction scheme and the elitist reservationmethod; and the adaptive mutation which used the Gaussian probability distribution to determine thevalues of the offspring produced by mutation mechanism. The examples are provided to verify thedesigned FDGA. The computation results indicate that the FDGA works very well in the field of formerror evaluation such as circularity evaluation.展开更多
Error analysis methods in frequency domain are developed in this paper for determining the characteristic root and transfer function errors when the linear multipass algorithms are used to solve linear differential eq...Error analysis methods in frequency domain are developed in this paper for determining the characteristic root and transfer function errors when the linear multipass algorithms are used to solve linear differential equations. The relation between the local truncation error in time domain and the error in frequency domain is established, which is the basis for developing the error estimation methods. The error estimation methods for the digital simulation model constructed by using the Runge-Kutta algorithms and the linear multistep predictor-corrector algorithms are also given.展开更多
Stewart平台被广泛应用于各类运动模拟器中,其中,位姿误差决定了模拟器的逼真程度。因此,针对平台在运动过程中因铰链间隙误差导致的位姿误差,设计了基于优化算法的误差补偿方案。首先,利用运动学反解求得在给定位姿轨迹下的驱动杆伸长...Stewart平台被广泛应用于各类运动模拟器中,其中,位姿误差决定了模拟器的逼真程度。因此,针对平台在运动过程中因铰链间隙误差导致的位姿误差,设计了基于优化算法的误差补偿方案。首先,利用运动学反解求得在给定位姿轨迹下的驱动杆伸长量。其次,利用矢量法构建位姿误差模型,研究位姿误差与驱动杆之间的关系,将位姿误差设计为以驱动杆为变量的目标函数,在此基础上,提出了融合莱维飞行和空间金字塔匹配混沌映射的改进型广义正态分布优化(improved generalized normal distribution optimization,IGNDO)算法,并求得目标函数最优值以及驱动杆最优解。最后,将最优解代入误差模型输出新的位姿误差,并与理论误差进行对比,验证了算法的有效性。同时,将IGNDO算法与现有算法进行比较,发现位姿误差能减小1-2个量级。展开更多
摘要In this paper, a class of generalized strongly nonlinear quasivariational inclusions are studied. By using the properties of the resolvent operator associated with a maximal monotone; mapping in Hilbert space, an existence theorem of solutions for generalized strongly nonlinear quasivariational inclusion is established and a new proximal point algorithm with errors is suggested for finding approximate solutions which strongly converge to the exact solution of the generalized strongly, nonlinear quasivariational inclusion. As special cases, some known results in this field are also discussed.
基金supported by the Joint Civil Aviation Fund of National Natural Science Foundation of China(Nos.U1533108 and U1233112)
摘要The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location performance of the time sum of arrival(TSOA) algorithm from the root mean square error(RMSE) and geometric dilution of precision(GDOP) in additive white Gaussian noise(AWGN) environment. The TSOA localization model is constructed. Using it, the distribution of location ambiguity region is presented with 4-base stations. And then, the location performance analysis is started from the 4-base stations with calculating the RMSE and GDOP variation. Subsequently, when the location parameters are changed in number of base stations, base station layout and so on, the performance changing patterns of the TSOA location algorithm are shown. So, the TSOA location characteristics and performance are revealed. From the RMSE and GDOP state changing trend, the anti-noise performance and robustness of the TSOA localization algorithm are proved. The TSOA anti-noise performance will be used for reducing the blind-zone and the false location rate of MLAT systems.
摘要According to the test data of subdivision errors in the measuring cycle of angular measuring system, the characteristics of subdivision errors generated by this system are analyzed. It is found that the subdivision errors are mainly due to the rotary-type inductosyn itself. For the characteristic of cyclical change, the subdivision errors in other measuring cycles can be compensated by the subdivision error model in one measuring cycle. Using the measured error data as training samples, combining GA and BP algorithm, an ANN model of subdivision error is designed. Simulation results indicate that GA reduces the uncertainty in the training process of the ANN model, and enhances the generalization of the model. Compared with the error model based on the least-mean-squared method, the designed ANN model of subdivision errors can achieve higher compensating precision.
基金The project is supported by National Natural Science Foundation of China(No.59975025).
摘要A genetic algorithm(GA)-based new method is designed to evaluate thecircularity error of mechanical parts. The method uses the capability of nonlinear optimization ofGA to search for the optimal solution of circularity error. The finely-designed GA (FDGA)characterized dynamical bisexual recombination and Gaussian mutation. The mathematical model of thenonlinear problem is given. The implementation details in FDGA are described such as the crossoveror recombination mechanism which utilized a bisexual reproduction scheme and the elitist reservationmethod; and the adaptive mutation which used the Gaussian probability distribution to determine thevalues of the offspring produced by mutation mechanism. The examples are provided to verify thedesigned FDGA. The computation results indicate that the FDGA works very well in the field of formerror evaluation such as circularity evaluation.
基金This project was supported by the National Natural Science Foundation of China (No. 19871080).
摘要Error analysis methods in frequency domain are developed in this paper for determining the characteristic root and transfer function errors when the linear multipass algorithms are used to solve linear differential equations. The relation between the local truncation error in time domain and the error in frequency domain is established, which is the basis for developing the error estimation methods. The error estimation methods for the digital simulation model constructed by using the Runge-Kutta algorithms and the linear multistep predictor-corrector algorithms are also given.
摘要Stewart平台被广泛应用于各类运动模拟器中,其中,位姿误差决定了模拟器的逼真程度。因此,针对平台在运动过程中因铰链间隙误差导致的位姿误差,设计了基于优化算法的误差补偿方案。首先,利用运动学反解求得在给定位姿轨迹下的驱动杆伸长量。其次,利用矢量法构建位姿误差模型,研究位姿误差与驱动杆之间的关系,将位姿误差设计为以驱动杆为变量的目标函数,在此基础上,提出了融合莱维飞行和空间金字塔匹配混沌映射的改进型广义正态分布优化(improved generalized normal distribution optimization,IGNDO)算法,并求得目标函数最优值以及驱动杆最优解。最后,将最优解代入误差模型输出新的位姿误差,并与理论误差进行对比,验证了算法的有效性。同时,将IGNDO算法与现有算法进行比较,发现位姿误差能减小1-2个量级。