This paper is concerned with the optimal state estimation problem under linear dynamic systems when the sampling rates of different sensors are different. The noises of different sensors are cross-correlated and coupl...
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This paper aims to address the robust control problem of rigid spacecraft attitude maneuvers in the presence of inertia matrix uncertainty and external disturbance. A back-stepping based adaptive sliding mode control ...
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This paper aims to present an improved adaptive sliding mode control (ASMC) design for rigid spacecraft attitude maneuvers. An adaptive scheme is proposed for the switching gain calculation when the upper bound of the...
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For indoor application,which is an entirely GPS-denied environment,visual simultaneous localization and mapping(SLAM) facilitates the real autonomy of unmanned aerial vehicle(UAV) but raises the challenging requiremen...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
For indoor application,which is an entirely GPS-denied environment,visual simultaneous localization and mapping(SLAM) facilitates the real autonomy of unmanned aerial vehicle(UAV) but raises the challenging requirement on accurate localization with low computational *** address this difficulty,a stereo-camera based SLAM system is proposed by applying Entropy theory to *** an extension to ORB-SLAM3,the additional entropy decision module and map processor are specifically *** decision module can improve computing efficiency by deciding whether keyframes or extra optimization should be ***,the map processor is targeted at loading and maintaining the prior map whenever *** results in indoor laboratory environment show that the developed system can achieve the superior localization accuracy in more efficient computation manner with smaller size of mapping compared with ***,the map can be effectively expanded and corrected even when prior information is invalid,greatly increasing the robustness of SLAM system.
The segmentation of the medical image faces the challenges of the existence of large number of diverse structures of human anatomy and inevitable artifacts induced from the imaging procedure. In this paper we treat so...
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This paper presents a 3D online path planning algorithm for unmanned aerial vehicle (UAV) flying in partially known hostile environment. In order to provide a smooth fight route for UAV, the algorithm adopts B-Spline ...
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This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics differen...
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This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality.
The assessment of aircraft damage is a key technology in modern flight missions. For a kind of ultra low altitude aircraft, simulation study of the damage caused by the prefabricated fragments is carried out, which is...
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Accurate dynamic state estimation plays an important role in power systems. Although various filtering algorithms, such as unscented Kalman filter (UKF) and particle filter (PF), have been proposed based on phasor mea...
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state estimation and fault diagnosis are essential topics for dynamic *** Kalman fllter(UKF) has been widely applied in nonlinear *** classical UKF algorithm is built on the premise that process noise and measuremen...
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ISBN:
(纸本)9781538629185
state estimation and fault diagnosis are essential topics for dynamic *** Kalman fllter(UKF) has been widely applied in nonlinear *** classical UKF algorithm is built on the premise that process noise and measurement noise is *** practical problems,this assumption is not always *** addition,due to the limitation of communication and sensor fault,etc.,data missing or unreliable measurements will happen ***,it is very important to study the state estimation of nonlinear systems with unreliable measurements and correlated *** this paper,an UKF based state estimation algorithm with unreliable observations under correlated noise is presented.A numerical example is given to show the feasibility and effectiveness of the presented algorithm.
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