Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Highly active sites of low spin FeⅡN4species:The identification and the ORR performance

Over recent years,catalytic materials of Fe-N-C species have been recognized being active for oxygen reduction reaction(ORR).However,the identification of active site remains challenging as it generally involves a pyrolysis process and mixed components being obtained.Herein Fe₃C/C and Fe₂N/C samples were synthesized by temperature programmed reduction of Fe precursors in 15%CH₄/H₂and pure NH₃,respectively.By acid leaching of Fe₂N/C sample,only single sites of FeN₄species were presented,providing an ideal model for identification of catalytic functions of the single sites of FeN₄in ORR.A correlation was conducted between the concentration of Fe^ⅡN₄in low spin state by Mossbauer spectra and the kinetic current density at 0.8 V in alkaline media,and such a structure-performance correlation assures the catalytic roles of low spin Fe^ⅡN₄ species as highly active sites for the ORR.     

Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein–Wiener system based on the key-term separation

The identification of the Hammerstein–Wiener (H-W) systems based on the nonuniform input–output dataset remains a challenging problem. This article studies the identification problem of a periodically nonuniformly sampled-data H-W system. In addition, the product terms of the parameters in the H-W system are inevitable. In order to solve the problem, the key-term separation is applied and two algorithms are proposed. One is the key-term-based forgetting factor stochastic gradient (KT-FFSG) algorithm based on the gradient search. The other is the key-term-based hierarchical forgetting factor stochastic gradient (KT-HFFSG) algorithm. Compared with the KT-FFSG algorithm, the KT-HFFSG algorithm gives more accurate estimates. The simulation results indicate that the proposed algorithms are effective.     

Performance investigation on a novel 3D wave flow channel design for PEMFC

Flow field structure can largely determine the output performance of Polymer electrolyte membrane fuel cell. Excellent channel configuration accelerates electrochemical reactions in the catalytic layer, effectively avoiding flooding on the cathode side. In present study, a three-dimensional, multi-phase model of PEMFC with a 3D wave flow channel is established. CFD method is applied to optimize the geometry constructions of three-dimensional wave flow channels. The results reveal that 3D wave flow channel is overall better than straight channel in promoting reactant gases transport, removing liquid water accumulated in microporous layer and avoiding thermal stress concentration in the membrane. Moreover, results show the optimal flow channel minimum depth and wave length of the 3D wave flow channel are 0.45 mm and 2 mm, respectively. Due to the periodic geometric characteristics of the wave channel, the convective mass transfer is introduced, improving gas flow rate in through-plane direction. Furthermore, when the cell output voltage is 0.4 V, the current density in the novel channel is 23.8% higher than that of conventional channel.     

Fabrication strategies and application fields of novel 2D Ti3C2Tx (MXene) composite hydrogels: A mini-review

Ti₃C₂T_x (MXene), a new kind of 2D ceramic nanosheets, is receiving more and more attention in the fields of medicine, biology, energy, electronics, etc. However, the preparation and application of MXene in hydrogel is still in its infancy period. Here, we review the latest progress (after 2018) related to MXene hydrogels in time. Aiming at the key issue of the dispersion stability of MXene in hydrogel systems, the preparation strategy, mechanism, advantages and disadvantages of MXene hydrogels are sorted out in detail, and the potential application prospects of MXene composite hydrogel are introduced. Finally, future viewpoints are put forward for the dispersion stability challenges that need solving in the design of MXene hydrogel.     

Improved Input and State Estimation for Linear Stochastic Systems with Direct Feedthrough

This paper is concerned with the problem of joint input and state estimation for linear stochastic systems with direct feedthrough. Based on the fact that each unknown input between any two time steps is always bounded, a novel improved algorithm is proposed. Compared with existing results, this algorithm can effectively enhance estimation accuracy. Moreover, the stability of the algorithm is also discussed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.