智能飞行器在军用和民用领域发挥着越来越重要的作用.在飞行过程中经常会出现累积的定位误差并且飞行到达应用场景时有定位精度要求,故需要对飞行轨迹进行适当的位置校正.为此,提出了一种在复杂条件下的智能飞行器航迹规划方法,利用基

The water droplet's dripping path is simulated by dripping algorithms and applied in many fields. In image segmentation, droplets directed by a traditional dripping algorithm may either be trapped in a dead cycle or forced traversing obstacles. To solve this problem, we first propose an improved dripping algorithm based on modeling the backflow of a water droplet. Instead of trapping, the improved algorithm guides the water droplet flow back for dripping opportunities. When blocked by both sides like falling into a low-lying 'shallow pit', we further propose to improve the dripping algorithm based on modeling the splashing of water droplets. This improvement allows water droplets to splash one pixel higher for escaping the 'shallow pit'. Experiments in image segmentation of Guqin music notations validate the proposed method and demonstrate its advantages over traditional dripping algorithms. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

Eye-in-hand systems have received significant attention for the task of approaching an object identi-fied by its reference image shown in advance. Image based visual servoing (VS) methods demonstrate robustness to image noises, but encounter difficulties especially when camera displacement is large. More challenges exist when the object is cylindrical with less texture. This paper proposes new feature set and pertinent trajectory planning scheme to achieve a convergent path with tolerable violation of camera field of view (FOV) limits, allowing transient loss of part of the observed object. Specifically, new features and interaction matrices are developed to achieve global convergence. Feature trajectories are then planned with tolerable FOV violation through a constrained nonlinear minimization path-planning technique. They are later tracked via an adapted IBVS controller in a switching manner. Simulation with two views of a real drinking vessel validates the proposed method and demonstrates its adaption to partial FOV violation.(c) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

This paper addresses the problem of determining the peak of the response to a linear time-invariant (LTI) signal of a linear system whose system matrices are rational functions of an uncertainty vector constrained into a convex bounded polytope. The uncertainty can be time-invariant, bounded-rate time-varying or arbitrarily time-varying. A novel approach based on linear matrix inequalities (LMIs) is proposed for obtaining upper bounds of the sought peak based on the construction of a structured polynomial Lyapunov function in the state and in the uncertainty. A priori and a posteriori conditions for establishing optimality of the obtained upper bounds are also provided. As shown by some numerical examples, which includes the model of an electric circuit, the proposed approach may have significant advantages with respect to the existing methods in terms of conservatism or computational burden.

The large proportion of asymptomatic patients is the major cause leading to the COVID-19 pandemic which is still a significant threat to the whole world. A six-dimensional ODE system (SEIAQR epidemical model) is established to study the dynamics of COVID-19 spreading considering infection by exposed, infected, and asymptomatic cases. The basic reproduction number derived from the model is more comprehensive including the contribution from the exposed, infected, and asymptomatic patients. For this more complex six-dimensional ODE system, we investigate the global and local stability of disease-free equilibrium, as well as the endemic equilibrium, whereas most studies overlooked asymptomatic infection or some other virus transmission features. In the sensitivity analysis, the parameters related to the asymptomatic play a significant role not only in the basic reproduction number R-0. It is also found that the asymptomatic infection greatly affected the endemic equilibrium. Either in completely eradicating the disease or achieving a more realistic goal to reduce the COVID-19 cases in an endemic equilibrium, the importance of controlling the asymptomatic infection should be emphasized. The three-dimensional phase diagrams demonstrate the convergence point of the COVID-19 spreading under different initial conditions. In particular, massive infections will occur as shown in the phase diagram quantitatively in the case R-0 > 1. Moreover, two four-dimensional contour maps of R-t are given varying with different parameters, which can offer better intuitive instructions on the control of the pandemic by adjusting policy-related parameters.