The armored vehicle power compartment is an organic complex that includes various components and subsystems that generate, convert, transmit, consume and manage the energy required for the vehicle to travel. Given the...
详细信息
The armored vehicle power compartment is an organic complex that includes various components and subsystems that generate, convert, transmit, consume and manage the energy required for the vehicle to travel. Given the large size, heavy weight, and complex structure of the power compartment, and the fact that most armored vehicles operate in remote areas, there is a need for high-efficiency testing in the field of modern special equipment. To address this, this paper focuses on the armored vehicle power compartment and designs a portable in-situ start-stop test tooling control system, tailored to actual engineering needs. The control system, paired with a corresponding power supply and distribution battery cabinet, controls the armored vehicle's power compartment. It employs STM32F407VET6 and SPC560P50L3BEABR as the core microcontrollers. Voltage output from the power supply and distribution battery cabinet is managed via the CAN bus to ensure precise, point-to-point power delivery to the motors in the power compartment. Subsequently, control instructions and test cases are transmitted to the motors using the FlexRay bus. Real-time data on the power compartment's operating parameters are collected to enable users to analyze any discrepancies between the actual and expected outputs of the power compartment, thus facilitating convenient and efficient performance testing.
It is crucial to balance accuracy and beyond-accuracy indicators in recommendations through multi-objective optimization (MOO) methods. Existing multi-objective recommendation methods have several issues: they cannot ...
详细信息
In this thesis, for second-order multi-agent systems with nonlinear kinetics, the event-triggered fixed-time consensus problem is researched. Firstly, we give the state error between agents, and design the control pro...
详细信息
The paper develops a novel framework of consensus control with fault-estimation-in-the-loop for multi-agent systems(MASs)in the presence of faults.A dynamic event-triggered protocol(DETP)by adding an auxiliary variabl...
详细信息
The paper develops a novel framework of consensus control with fault-estimation-in-the-loop for multi-agent systems(MASs)in the presence of faults.A dynamic event-triggered protocol(DETP)by adding an auxiliary variable is utilized to improve the utilization of communication ***,a novel estimator with a noise bias is put forward to estimate the existed fault and then a consensus controller with fault compensation(FC)is adopted to realize the demand of reliability and safety of addressed ***,a novel consensus control framework with fault-estimation-in-the-loop is developed to achieve the predetermined consensus performance with the l_(2)-l_(∞)constraint by employing the variance analysis and the Lyapunov stability ***,the desired estimator and controller gains are obtained in light of the solution to an algebraic matrix equation and a linear matrix inequality in a recursive way,***,a simulation result is employed to verify the usefulness of the proposed design framework.
Aiming at the problem that the traditional time series prediction model could not make full use of the relevant information of time series and the interpretability is poor,a time series prediction model based on fuzzy...
详细信息
ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Aiming at the problem that the traditional time series prediction model could not make full use of the relevant information of time series and the interpretability is poor,a time series prediction model based on fuzzy cognitive graph modeling is proposed in this paper and the boiler furnace temperature prediction is taken as an example for ***,this paper divides the fuzzification of time series data of boiler furnace temperature into multiple subsets,and establishes a fuzzy cognitive map model on each ***,the prediction results of each sub model are fused to obtain the accurate prediction value,prediction interval and semantic interpretation corresponding to the prediction value of furnace temperature.
In this paper,an improved stochastic algebraic Riccati(SAR) iterative algorithm based on numerical iterative is adopted to solve the stochastic linear quadratic optimal tracking(SLQT) control problem for stochastic di...
详细信息
ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In this paper,an improved stochastic algebraic Riccati(SAR) iterative algorithm based on numerical iterative is adopted to solve the stochastic linear quadratic optimal tracking(SLQT) control problem for stochastic discrete-time ***,an augmented system composed of the stochastic discrete-time system and command generator is ***,the augmented stochastic algebraic Riccati equation(SARE) is derived based on the augmented system and the corresponding SAR iterative algorithm is obtained according to the idea of value iteration(VI) ***,an improved SAR iterative algorithm is raised based on the given SAR iterative algorithm and combined with the numerical iterative ***,simulation results verify the effectiveness of the proposed algorithm.
Speech is more affected by the environment and noise, while the visual information corresponding to the speaker, such as lip movement and facial appearance are more robust. In this paper, a vision-guided speaker embed...
详细信息
For real-time measurement of crystal size distribution(CSD) by in-situ captured crystal images,a deep-learning based image analysis method is proposed to improve measurement accuracy and efficiency,based on the well r...
详细信息
ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
For real-time measurement of crystal size distribution(CSD) by in-situ captured crystal images,a deep-learning based image analysis method is proposed to improve measurement accuracy and efficiency,based on the well recognized maskregional convolutional neural network(Mask R-CNN).An automatic dataset labelling algorithm is established to facilitate preparing the training dataset that is required to include a large number of crystal image samples for effective deep ***,an image thresholding segmentation algorithm is introduced to extract the region of interest(ROI) in each crystal image sample for training the Mask R-CNN,such that improved segmentation accuracy and efficiency could be obtained for online image analysis to measure CSD during a crystallization *** results on measuring the crystallization process of β form L-glutamic acid(β-LGA) are shown to verify the effectiveness and advantage of the proposed method.
Safe driving has been the core of the traditional traffic, it is also a top priority for the future of autonomous driving. In recent years, with the development of target detection, a large number of proven technique ...
详细信息
Named entity recognition (NER) is a fundamental task in natural language processing and a key technology for building knowledge graphs. However, the performance of NER is often limited by domain-specific characteristi...
详细信息
暂无评论