Bionic robotic fish has a significant impact on design and control of innovative underwater robots capable of both rapid swimming and high maneuverability. This paper explores the relationship between Central Pattern ...
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Bionic robotic fish has a significant impact on design and control of innovative underwater robots capable of both rapid swimming and high maneuverability. This paper explores the relationship between Central Pattern Generator (CPG) based locomotion control and energy consumption of a miniature self-propelled robotic fish. To this end, a real-time energy measurement system compatible with the CPG-based locomotion control is firstly built on an embedded system. Then, tests are conducted on the untethered actual robot. The results indicate that different CPG feature parameters involving amplitude, frequency, and phase lag play distinct roles in energy consumption under different swimming gaits. Specifically, energy consumption is positively correlated with the changes in the amplitude and frequency of CPGs, whereas the phase lag of CPGs has little influence on the energy consumption. It may offer important inspiration for improving energy efficiency and locomotion performance of versatile swimming gaits.
With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been...
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With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been paid to its entertainment and social functions. Considering the openness and interoperability of metaverses, the market of quality inspection promises explosive growth. In this paper, taking advantage of metaverses, we first propose the concept of Automated Quality Inspection(Auto QI), which performs integrated inspection covering the entire manufacturing process, including Quality of Materials, Quality of Manufacturing(Qo M), Quality of Products, Quality of Processes(Qo P), Quality of systems, and Quality of Services(Qo S). Based on the scenarios engineering theory, we discuss how to perform interactions between metaverses and the physical world for virtual design instruction and physical validation feedback. Then we introduce a bottomup inspection device development workflow with productivity tools offered by metaverses, making development more effective and efficient than ever. As the core of quality inspection,we propose Quality Transformers to complete detection task,while federated learning is integrated to regulate data *** summary, we point out the development directions of quality inspection under metaverse tide.
Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to direct...
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Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.
This paper studies the distributed average tracking problem for multiple time-varying signals with nonlinear *** only on relative output measurements, a pair of continuous algorithms with, respectively, static and ada...
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ISBN:
(纸本)9781467374439
This paper studies the distributed average tracking problem for multiple time-varying signals with nonlinear *** only on relative output measurements, a pair of continuous algorithms with, respectively, static and adaptive coupling strengths are designed and utilized. From the concept of boundary layer approach, the proposed continuous algorithm with static coupling strengths can asymptotically obtain the average value of the multiple reference signals without chattering ***, a simulation example is presented to show the validity of the theoretical results.
An ab initio core-shell model is proposed to evaluate the surface effect in bending nanowires,in which the elastic modulus depends on the surface relaxation and deformation induced by external *** using first-principl...
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An ab initio core-shell model is proposed to evaluate the surface effect in bending nanowires,in which the elastic modulus depends on the surface relaxation and deformation induced by external *** using first-principles calculations based on the density functional theory(DFT),the surface and bulk properties are calculated for Ag,Pb,and Si *** obtained theoretical predictions of the effective Young’s modulus of nanowires agree well with the experimental data,which shows that the fixed-fixed nanowire is stiffened and the cantilevered nanowire is softened as the characteristic size of the cross section ***,the contrastive analysis on the two kinds of nanowires demonstrates that increasing the nanowire aspect ratio would enhance the surface *** present results could be helpful for understanding the size effect in nanowires and designing nanobeam-based devices in nanoelectromechanical systems(NEMSs).
This paper presents an adaptive equivalent-input-disturbance(AEID)approach that contains a new adjustable gain to improve disturbance-rejection performance.A linear matrix inequality is derived to design the parameter...
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This paper presents an adaptive equivalent-input-disturbance(AEID)approach that contains a new adjustable gain to improve disturbance-rejection performance.A linear matrix inequality is derived to design the parameters of a control *** adaptive law for the adjustable gain is presented based on the combination of the root locus method and Lyapunov stability theory to guarantee the stability of the AEID-based *** adjustable gain is limited in an allowable range and the information for adjusting is obtained from the state of the *** results show that the method is effective and robust.A comparison with the conventional EID approach demonstrates the validity and superiority of the method.
This paper investigates the asymptotical stability for discrete-time Cohen-Grossberg neural networks with both timevarying and distributed delays. By constructing a novel Lyapunov-Krasovskii functional and introducing...
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This paper presents an enhanced friction compensation anti-disturbance control strategy for improving the speed regulation control performance of a permanent magnet synchronous motor operating in low-speed mode. This ...
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A modified extended state observer (ESO) based rotor position algorithm is proposed for improving low speed regulation control performance. The speed signal is often obtained by differentiating the position signal. Ho...
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Based on the recent success of Low-Rank matrix Representation(LRR),we propose a novel classification method for robust face recognition,named LRR-based Classification(LRRC).By the ideal that if each data class is line...
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ISBN:
(纸本)9781479947249
Based on the recent success of Low-Rank matrix Representation(LRR),we propose a novel classification method for robust face recognition,named LRR-based Classification(LRRC).By the ideal that if each data class is linearly spanned by a subspace of unknown dimensions and the data are noiseless,the lowest-rank representations of a set of test vector samples with respect to a set of training vector samples have the nature of being both dense for within-class affinity and almost zero for between-class ***,the LRR exactly reveals the classification of the *** experimental results demonstrate that LRRC has competitive with state-of-the-art classification methods.
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