When installing radio-based train controlsystems for areas with many lines such as an urban areas, there is concern about the lack of frequency channels. We propose a method of transmitting information to multiple tr...
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The inverse and direct piezoelectric and circuit coupling are widely observed in advanced electro-mechanical systems such as piezoelectric energy *** strongly coupled analysis methods based on direct numerical modelin...
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The inverse and direct piezoelectric and circuit coupling are widely observed in advanced electro-mechanical systems such as piezoelectric energy *** strongly coupled analysis methods based on direct numerical modeling for this phenomenon can be classified into partitioned or monolithic *** formulation has its advantages and disadvantages,and the choice depends on the characteristics of each coupled *** study proposes a new option:a coupled analysis strategy that combines the best features of the existing formulations,namely,the hybrid partitioned-monolithic *** analysis of inverse piezoelectricity and the monolithic analysis of direct piezoelectric and circuit interaction are strongly coupled using a partitioned iterative hierarchical *** a typical benchmark problem of a piezoelectric energy harvester,this research compares the results from the proposed method to those from the conventional strongly coupled partitioned iterative method,discussing the accuracy,stability,and computational *** proposed hybrid concept is effective for coupled multi-physics problems,including various coupling conditions.
Maintaining contact stability is crucial when the aerial manipulator interacts with the surrounding environment. In this paper, a novel output feedback framework based on a characteristic model is proposed to improve ...
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Maintaining contact stability is crucial when the aerial manipulator interacts with the surrounding environment. In this paper, a novel output feedback framework based on a characteristic model is proposed to improve the contact stability of the aerial manipulator. First, only position measurements of the aerial manipulator are introduced to design the practical finite-time command filter-based force observer. Second, an attitude control architecture including characteristic modeling and controller design is presented. In the modeling part, input-output data is utilized to build the characteristic model with fewer parameters and a simpler structure than the traditional dynamic model. Different from conventional control methods, fewer feedback values,namely only angle information, are required for designing the controller in the controller part. In addition, the convergence of force estimation and the stability of the attitude control system are proved by the Lyapunov analysis. Numerical simulation comparisons are conducted to validate the effectiveness of the attitude controller and force observer. The comparative results demonstrate that the tracking error of x and θ channels decreases at least 10.62% and 10.53% under disturbances and the force estimation precision increases at least 45.19% in the different environmental stiffness. Finally, physical flight experiments are conducted to validate the effectiveness of the proposed framework by a self-built aerial manipulator platform.
This paper presents a novel approach for distributed model predictive control (MPC) for piecewise affine (PWA) systems. Existing approaches rely on solving mixed-integer optimization problems, requiring significant co...
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In this study, we propose an algorithm selection method based on coupling strength for the partitioned analysis ofstructure-piezoelectric-circuit coupling, which includes two types of coupling or inverse and direct pi...
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In this study, we propose an algorithm selection method based on coupling strength for the partitioned analysis ofstructure-piezoelectric-circuit coupling, which includes two types of coupling or inverse and direct piezoelectriccoupling and direct piezoelectric and circuit coupling. In the proposed method, implicit and explicit formulationsare used for strong and weak coupling, respectively. Three feasible partitioned algorithms are generated, namely(1) a strongly coupled algorithm that uses a fully implicit formulation for both types of coupling, (2) a weaklycoupled algorithm that uses a fully explicit formulation for both types of coupling, and (3) a partially stronglycoupled and partially weakly coupled algorithm that uses an implicit formulation and an explicit formulation forthe two types of coupling, *** examples using a piezoelectric energy harvester,which is a typicalstructure-piezoelectric-circuit coupling problem, demonstrate that the proposed method selects the most costeffectivealgorithm.
Thanks to the emerging integration of algorithms and simulators, recent Driving Simulators (DS) find enormous potential in applications like advanced driver-assistance devices, analysis of driver’s behaviours, resear...
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Thanks to the emerging integration of algorithms and simulators, recent Driving Simulators (DS) find enormous potential in applications like advanced driver-assistance devices, analysis of driver’s behaviours, research and development of new vehicles and even for entertainment purposes. Driving simulators have been developed to reduce the cost of field studies, allow more flexible control over circumstances and measurements, and safely present hazardous conditions. The major challenge in a driving simulator is to reproduce realistic motions within hardware constraints. Motion Cueing Algorithm (MCA) guarantees a realistic motion perception in the simulator. However, the complex nature of the human perception system makes MCA implementation challenging. The present research aims to improve the performance of driving simulators by proposing and implementing the MCA algorithm as a control problem. The approach is realized using an actual vehicle model integrated with a detailed model of the human vestibular system, which accurately reproduces the driver’s perception. These perception motion signals are compared with simulated ones. A 2-DOF stabilized platform model is used to test the results from the two proposed control strategies, Proportional Integrator and Derivative (PID) and Model Predictive control (MPC).
The importance of Model Predictive control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge...
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The importance of Model Predictive control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge prevent an exact mathematical description of the *** methods provide a promising solution to this issue through their capacity to identify the system’s comportment using the fit between model output and observed *** this paper,we introduce an application of Constrained Model Predictive control(CMPC)for a greenhouse temperature and relative *** this purpose,two Multi Input Single Output(MISO)systems,using Numerical Subspace State Space System Identification(N4SID)algorithm,are firstly suggested to identify the temperature and the relative humidity comportment to heating and ventilation *** this sense,linear state space models were adopted in order to evaluate the robustness of the control *** the system is identified,the MPC technique is applied for the temperature and the humidity *** results show that the regulation of the temperature and the relative humidity under constraints was guaranteed,both parameters respect the ranges 15℃≤T_(int)≤30℃and 50%≤H_(int)≤70%*** the other hand,the control signals uf and uh applied to the fan and the heater,respect the hard constraints notion,the control signals for the fan and the heater did not exceed 0≤uf≤4.3 Volts and 0≤uh≤5 Volts,respectively,which proves the effectiveness of the MPC and the tracking ***,we show that with the proposed technique,using a new optimization toolbox,the computational complexity has been significantly *** greenhouse in question is devoted to Schefflera Arboricola cultivation.
In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked controlsystems. These systems require the transmission of ...
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In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked controlsystems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.
Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural net...
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Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social *** paper proposes a social robot detection method with the use of an improved neural ***,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships ***,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the ***,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph ***,social robots can be more accurately identified by combining user behavioral and relationship *** carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,*** with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two *** results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.
In this paper,the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess *** each system,a sensor will measure its state and transmits the data packets...
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In this paper,the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess *** each system,a sensor will measure its state and transmits the data packets through an unreliable channel which is vulnerable to be jammed by an *** limited communication bandwidth,only a subset of sensors are allowed for data transmission,and how to select the optimal one to maximize the accuracy of remote state estimation is the focus of the proposed *** authors first formulate this problem as a Markov decision process and investigate the existence of optimal ***,the authors demonstrate the piecewise monotonicity structure of optimal *** the difficulty of obtaining an optimal policy of large-scale problems,the authors develop a suboptimal heuristic policy based on the aforementioned policy structure and Whittle’s ***,a closed form of the indices is derived in order to reduce implementation complexity of proposed scheduling policy and numerical examples are provided to illustrate the proposed developed results.
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