ID 原文 译文
54707 实验结果表明,该算法能够适应目标的尺度变化,检测目标的丢失,提高了跟踪稳定性。 The experimental results show that the algorithm can adapt to the change of the scale of the target, detect the loss of the target, improve the tracking stability.
54708 针对现有扩展卡尔曼滤波算法在协同定位应用计算复杂的问题,提出一种基于联合分布状态的信息滤波算法,并将其运用在多机器人协同定位中。 In view of the existing extended kalman filtering algorithm in application co-location computing complex problems, put forward a kind of information filtering algorithm based on joint distribution state, and its use in multi-robot cooperative localization.
54709 从3个方面解决计算复杂的问题: Solve the problem of calculating complex from three aspects:
54710 第一,借鉴机器人同步构图与定位,利用联合分布状态将关键历史状态保留在滤波中,避免时间更新的复杂计算;第二,利用滤波信息参数的稀疏性,减小滤波所涉及的计算复杂度;第三,根据Cholesky矩阵分解的特殊性质,进一步减少计算复杂度,节省存储空间,简化通信管理,便于工作负载均衡分配。 first, draw lessons from robot synchronization composition and positioning, using the joint distribution status, keep the key historical status in filtering, avoid complex calculation time update;Second, make use of information filtering parameter is sparse, decreasing filtering computing complexity involved;Third, based on the special properties of the matrix Cholesky decomposition, further reduce the computational complexity, saving storage space, simplify the communication management, facilitate the distribution of workload balancing.
54711 理论分析与仿真结果表明,该方法在确保计算与存储复杂度的同时保证了估计精度和协同定位的有效性。 Theoretical analysis and simulation results show that the method in computing and storage complexity at the same time to ensure the effectiveness of the estimation precision and co-location.
54712 针对非线性系统的模型预测控制问题,提出了一种基于线性近似和神经网络逼近的控制算法。 Predictive control problem of nonlinear system model, this paper proposes a control algorithm based on linear approximation and the neural network approximation.
54713 用Taylor级数展开法对非线性系统进行线性近似时,要求对象系统中的非线性函数必须连续可微。 Using Taylor series expansion method for linear approximation of nonlinear system, the request object in the system must be continuously differentiable nonlinear function.
54714 为了突破这一限制,引入了Stirling插值公式线性近似法,拓展了可处理的非线性系统范围。 In order to break through the limit, Stirling interpolation formula of linear approximation method is introduced, expanding the scope can deal with nonlinear system.
54715 通过对线性化过程中产生的非线性高阶项进行径向基函数(radial basis function,RBF)神经网络逼近,显著提高了对象系统模型精确度。 Through the linearization of nonlinear higher order term of radial basis function (radial basis function, RBF) neural network approximation, significantly improve the object systems model accuracy.
54716 为了降低数值计算复杂度,将控制性能指标函数重构为易于处理的二次型最优化问题,通过对该二次型最优化问题的求解得到了最优控制序列。 To reduce the numerical computational complexity, the control performance index function reconstruction for easy handling of quadratic optimization problem, based on the quadratic optimization problem of solving the optimal control sequence.