Robust Leaderless Consensus of Uncertain Multiagent Systems with Fast Switching Topologies

This paper investigates the robust leaderless consensus problem of uncertain multiagent systems with directed fast switching topologies. The topologies are assumed to jointly contain a directed spanning tree. Based on a special property of the graph Laplacian matrix, the consensus problem is converted into a stabilization problem by performing a proper variable transformation. Averaging method is employed for analysis. It is proved that if the topologies switch sufficiently fast and the controllers are properly designed, the robust leaderless consensus can still be achieved even when all the possible topologies are unconnected in the switching time intervals. Finally, a numerical simulation is provided to illustrate the effectiveness of the theoretical results

STF-based diagnosis of AUV thruster faults

The diagnosis of thruster faults of autonomous underwater vehicles is studied in this paper. Based on the theory of strong tracking filter (STF), the AUV motion model and the thruster fault model are established. The STFs are designed for each thruster for the purpose of fault diagnosis. The AUV state and the fault deviation of the thruster are estimated online before the thruster faults are diagnosed based on residual analysis. The simulation experiments were conducted to verify the feasibility and effectiveness of the STF-based diagnosis of AUV thruster faults

Evaluation of Bletilla striata Polysaccharide Deproteinized System Based on Entropy Weighted TOPSIS Model

The entropy TOPSIS model was used to compare the effects of Sevage method， acetonitrile method and trichloroacetic acid (TCA) method for removaling crude Bletilla striata polysaccharide (BSP) protein, and to explore the rationality of entropy TOPSIS for BSP deproteinization system evaluation. Based on the comprehensive score of BSP retention rate and protein removal rate, the optimal treatment conditions were screened out. Nine evaluation indicators including monosaccharide components, oxidative radical scavenging ability (ORAC), and half scavenging concentration of DPPH radicals (IC50) were constructed. Supplemented by UV and FTIR, the entropy TOPSIS was used to evaluate the results of three BSP deproteinization programs. After comprehensive score, the best extraction times of sevage method was 1 time. At same time, the protein removal rate was 22.9%, and the polysaccharide retention rate was 99.11%. The optimal mass concentration of the TCA method was 10%, when the protein removal rate was 70.64%, and the polysaccharide retention rate was 70.03%. Compared with the ORAC values and IC50 of the three polysaccharide, it was found that the value of polysaccharide ORAC treated by the acetonitrile method was higher than that of the positive control group (P<0.05), and the polysaccharides treated by the Sevage method had the strongest antioxidant activity. The BSP deproteinization evaluation system was analyzed by the entropy TOPSIS model, and the sevage method deproteinization effect was the best and the expected result. The results showed that the entropy TOPSIS model could be used in the evaluation of BSP deproteinization system

Preparation and Performance Study of the Anodic Catalyst Layer via Doctor Blade Coating for PEM Water Electrolysis

The membrane electrode assembly (MEA) is the core component of proton exchange membrane (PEM) water electrolysis cell, which provides a place for water decomposition to generate hydrogen and oxygen. The microstructure, thickness, IrO2 loading as well as the uniformity and quality of the anodic catalyst layer (ACL) have great influence on the performance of PEM water electrolysis cell. Aiming at providing an effective and low-cost fabrication method for MEA, the purpose of this work is to optimize the catalyst ink formulation and achieve the ink properties required to form an adherent and continuous layer with doctor blade coating method. The ink formulation (e.g., isopropanol/H2O of solvents and solids content) were adjusted, and the doctor blade thickness was optimized. The porous structure and the thickness of the doctor blade coating ACL were further confirmed with the in-plane and the cross-sectional SEM analyses. Finally, the effect of the ink formulation and the doctor blade thickness of the ACL on the cell performance were characterized in a PEM electrolyzer under ambient pressure at 80 &deg;C. Overall, the optimized doctor blade coating ACL showed comparable performance to that prepared with the spraying method. It is proved that the doctor blade coating is capable of high-uniformity coating

A Model Free Adaptive Scheme for Integrated Control of Civil Aircraft Trajectory and Attitude

The adaptive trajectory and attitude control is essential for the four-dimensional (4D) trajectory operation of civil aircraft in symmetric thrust flight. In this work, an integrated trajectory and attitude control scheme is proposed based on the =multi-input multi-output (MIMO) model free adaptive control (MFAC) method. First, the full-form dynamic linearization technique is adopted to build the equivalent data model of aircraft. Also, the MIMO MFAC scheme with saturation constraint is designed to achieve an accurate tracking control for a given 4D trajectory and attitude. Besides, the performance limitations of aircraft are taken into consideration, and the MIMO MFAC scheme with hard constraints is designed. In addition, to improve the simulation efficiency, a control scheme with mixed constraints, i.e., saturation and hard constraints, is further proposed. It can be seen from the simulation results that the proposed method can perform an integrated control of the aircraft 4D trajectory and attitude without precise modeling, and the control performance is better than that of the model-based control method in terms of flight altitude and yaw angle control. The integrated data-driven control scheme proposed in this paper provides a theoretical solution for the precise operation of aircraft under 4D trajectory

DRL-based Resource Allocation in Remote State Estimation

Remote state estimation, where sensors send their measurements of distributed dynamic plants to a remote estimator over shared wireless resources, is essential for mission-critical applications of Industry 4.0. Existing algorithms on dynamic radio resource allocation for remote estimation systems assumed oversimplified wireless communications models and can only work for small-scale settings. In this work, we consider remote estimation systems with practical wireless models over the orthogonal multiple-access and non-orthogonal multiple-access schemes. We derive necessary and sufficient conditions under which remote estimation systems can be stabilized. The conditions are described in terms of the transmission power budget, channel statistics, and plants' parameters. For each multiple-access scheme, we formulate a novel dynamic resource allocation problem as a decision-making problem for achieving the minimum overall long-term average estimation mean-square error. Both the estimation quality and the channel quality states are taken into account for decision making. We systematically investigated the problems under different multiple-access schemes with large discrete, hybrid discrete-and-continuous, and continuous action spaces, respectively. We propose novel action-space compression methods and develop advanced deep reinforcement learning algorithms to solve the problems. Numerical results show that our algorithms solve the resource allocation problems effectively and provide much better scalability than the literature.Comment: Paper submitted to IEEE for possible publication. arXiv admin note: text overlap with arXiv:2205.1186

Leader-Following Consensus of Multi-agent in Switching Networks with Time-Delay

This paper is devoted to the study of multi-agent consensus with a time-varying reference state in directed networks with both switching topology and constant time delay. Stability analysis is performed based on a proposed Lyapunov–Krasovskii function. Sufficient conditions based on linear matrix inequalities (LMIs) are given to guarantee multi-agent consensus on a time-vary reference state under arbitrary switching of the network topology even if the network communication is affected by time delay. Finally, simulation examples are given to validate the theoretical results. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.260

Local flux coordination and global gene expression regulation in metabolic modeling

Abstract Genome-scale metabolic networks (GSMs) are fundamental systems biology representations of a cell’s entire set of stoichiometrically balanced reactions. However, such static GSMs do not incorporate the functional organization of metabolic genes and their dynamic regulation (e.g., operons and regulons). Specifically, there are numerous topologically coupled local reactions through which fluxes are coordinated; the global growth state often dynamically regulates many gene expression of metabolic reactions via global transcription factor regulators. Here, we develop a GSM reconstruction method, Decrem, by integrating locally coupled reactions and global transcriptional regulation of metabolism by cell state. Decrem produces predictions of flux and growth rates, which are highly correlated with those experimentally measured in both wild-type and mutants of three model microorganisms Escherichia coli, Saccharomyces cerevisiae, and Bacillus subtilis under various conditions. More importantly, Decrem can also explain the observed growth rates by capturing the experimentally measured flux changes between wild-types and mutants. Overall, by identifying and incorporating locally organized and regulated functional modules into GSMs, Decrem achieves accurate predictions of phenotypes and has broad applications in bioengineering, synthetic biology, and microbial pathology

Stainless Steel-Supported Amorphous Nickel Phosphide/Nickel as an Electrocatalyst for Hydrogen Evolution Reaction

Recently, nickel phosphides (Ni-P) in an amorphous state have emerged as potential catalysts with high intrinsic activity and excellent electrochemical stability for hydrogen evolution reactions (HER). However, it still lacks a good strategy to prepare amorphous Ni-P with rich surface defects or structural boundaries, and it is also hard to construct a porous Ni-P layer with favorable electron transport and gas&ndash;liquid transport. Herein, an integrated porous electrode consisting of amorphous Ni-P and a Ni interlayer was successfully constructed on a 316L stainless steel felt (denoted as Ni-P/Ni-316L). The results demonstrated that the pH of the plating solution significantly affected the grain size, pore size and distribution, and roughness of the cell-like particle surface of the amorphous Ni-P layer. The Ni-P/Ni-316L prepared at pH = 3 presented the richest surface defects or structural boundaries as well as porous structure. As expected, the as-developed Ni-P/Ni-316L demonstrated the best kinetics, with &eta;10 of 73 mV and a Tafel slope of ca. 52 mV dec-1 for the HER among all the electrocatalysts prepared at various pH values. Furthermore, the Ni-P/Ni-316L exhibited comparable electrocatalytic HER performance and better durability than the commercial Pt (20 wt%)/C in a real water electrolysis cell, indicating that the non-precious metal-based Ni-P/Ni-316L is promising for large-scale processing and practical use