Trajectory planning for the unmanned vehicle in the complex environment has always been a challenging task. Planned trajectory with the corresponding target velocity or acceleration sequence must be collision-free gua...
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Deforestation is the primary source of global warming;traditional shelf lab.ls use paper to display the price of the products,and human forces play a pivotal role in updating the tags where the pandemic has strictly l...
Deforestation is the primary source of global warming;traditional shelf lab.ls use paper to display the price of the products,and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its *** technologies provide connectivity and a fast-updating system to eliminate the paper-based *** is one of the contenders to design the system for electronic shelf lab.ls(ESLs).In this paper,LoRa has been used to minify data losses and guarantee the successful decoding of the carrier *** data parallelism at the network server(NS) is used to distribute the data packets among the gateways(GWs) for concurrent transmissions to the end devices(EDs).The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and *** data rate(DR) and spreading factors(SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated *** orthogonality principles follow industrial,scientific,and medical regulations(ISM) to avoid data traffic *** under different duty cycles(DC) and bandwidth(BW) are examined to minify the network saturation and reduce the energy harvesting of the tags.
This paper is concerned with the controller design and the theoretical analysis for time-delay systems, a two degree of freedom (feedforward and feedback) control method is proposed, which combines advantages of the S...
This paper is concerned with the controller design and the theoretical analysis for time-delay systems, a two degree of freedom (feedforward and feedback) control method is proposed, which combines advantages of the Smith predictor and the active disturbance rejection control (ADRC). The feedforward part of controller is used to track the set point, the feedback part of controller (ADRC) is used to suppress interferences and the Smith predictor is used to correct time delay. The proposed control design is easy to tune parameters and has been proved to effectively controlsystems with large time delay. The bounded input bounded output (BIBO) stability of closed-loop system is verified. Finally, numerical simulations show the effectiveness and practicality of the proposed design.
In sequential recommender systems, the main problems are the long-tailed distribution of data and noise interference. A Contrastive Framework for Sequential Recommendation (CFSeRec) is proposed to solve these two prob...
In sequential recommender systems, the main problems are the long-tailed distribution of data and noise interference. A Contrastive Framework for Sequential Recommendation (CFSeRec) is proposed to solve these two problems respectively. Token shuffling and adversarial attack data augmentation methods are used in the framework to improve the quality and quantity of training data, so that the long-tailed problem is mitigated. Through the application of projection head method, the sequence representation becomes more general and robust, rather than just adapted to the task of contrastive learning. Therefore, the impact of noise on sequence recommender systems is effectively alleviated. Experiments on four public datasets show that CFSeRec achieves state-of-the-art performance in the metrics of hit ratio and normalized discounted cumulative gain, when comparing to the seven previous frameworks.
This paper investigates the recursive filtering (RF) problem for stochastic multi-rate (MR) systems, where the information transmission is regulated by an improved weighted try-once-discard protocol (IWTODP). In order...
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With the aim of 2-AMT electric vehicles, a comprehensive shift schedule that considers both power and economy is proposed. First, the objective function of the comprehensive shift schedule is constructed, which is the...
With the aim of 2-AMT electric vehicles, a comprehensive shift schedule that considers both power and economy is proposed. First, the objective function of the comprehensive shift schedule is constructed, which is the weighted sum of vehicle acceleration time and vehicle power consumption per unit distance. Second, Sparrow Search Algorithm is used to solve the objective function and obtain the comprehensive shift schedule. Finally, AVL Cruise simulation software is used to simulate vehicle dynamics and economy under an NEDC. The results show that the comprehensive shift schedule is similar to the optimal power shift schedule in terms of dynamic performance, and the economy is optimized by 3%. The feasibility of the comprehensive shift schedule is verified.
Many real-world optimization problems involve multiple conflicting objectives. Such problems are called multiobjective optimization problems(MOPs). Typically, MOPs have a set of so-called Pareto optimal solutions rath...
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Many real-world optimization problems involve multiple conflicting objectives. Such problems are called multiobjective optimization problems(MOPs). Typically, MOPs have a set of so-called Pareto optimal solutions rather than one unique optimal solution. To assist the decision maker(DM) in finding his/her most preferred solution, we propose an interactive multiobjective evolutionary algorithm(MOEA)called iDMOEA-εC, which utilizes the DM's preferences to compress the objective space directly and progressively for identifying the DM's preferred region. The proposed algorithm employs a state-of-the-art decomposition-based MOEA called DMOEA-εC as the search engine to search for solutions. DMOEA-εC decomposes an MOP into a series of scalar constrained subproblems using a set of evenly distributed upper bound vectors to approximate the entire Pareto front. To guide the population toward only the DM's preferred part on the Pareto front, an adaptive adjustment mechanism of the upper bound vectors and two-level feasibility rules are proposed and integrated into DMOEA-εC to control the spread of the population. To ease the DM's burden, only a small set of representative solutions is presented in each interaction to the DM,who is expected to specify a preferred one from the set. Furthermore, the proposed algorithm includes a two-stage selection procedure, allowing to elicit the DM's preferences as accurately as possible. To evaluate the performance of the proposed algorithm, it was compared with other interactive MOEAs in a series of experiments. The experimental results demonstrated the superiority of iDMOEA-εC over its competitors.
The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast response. However, due to the inherent nonlinearity of multiplication, it brings certain d...
The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast response. However, due to the inherent nonlinearity of multiplication, it brings certain difficulties to the control. The electric double-variable pump[1] is a dual-input single-output system, and it is a nonlinear system[2]. It is necessary to linearize the system or use a nonlinear control method to control and solve the control problem of the system. In this paper, an intelligentcontrol rule is proposed for the nonlinear problem of double input and single output. Through backstepping design[3], the nonlinear system is transformed into multiple linear subsystems. Then the original system is turned into two independent subsystems with single input and single output, which are controlled separately. The co-simulation platform based on AMESIM and Simulink[4] has been verified and compared with a single PID control algorithm to simulate the step response and sinusoidal tracking performance of the system. The results show that the response speed of the system has been greatly improved.
Safe and efficient decision-making and path planning is a challenging problem for autonomous driving in highway because of numerous dynamic vehicles around the ego-vehicle. For ego-vehicle driving on structured roads,...
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Uncontrolled intersections are important and challenging traffic scenarios for autonomous vehicles. Vehicles not only need to avoid collisions with dynamic vehicles instantaneously but also predict their behavior then...
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