Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Effects of Cooling Rate and Component on the Microstructure and Mechanical Properties of Mg–Zn–Y Alloys

The microstructure and mechanical properties of Mg–6Zn–1Y and Mg–6Zn–3Y(wt%) alloys under different cooling rates were investigated. The results show that the second dendrite arm spacing(SDAS) of Mg–6Zn–1Y and Mg–6Zn–3Y is reduced by 32 and 30% with increasing cooling rates(Rc) from 10.2 to 23 K/s, which can be predicted using a empirical model of SDAS=68 R 0:45:45cand SDAS=73 R 0c, respectively. The compressive strength of both alloys increases with increasing the cooling rate, which is attributed to the increase of volume fraction(Vf) of secondary phases under high cooling rate. The interaction of the cooling rate and component with SDAS has been theoretically analyzed using interdependence theory.     

A quarter century of wine pigment discovery

The red grape berry pigments, anthocyanins, were characterized in the early 20th century, but investigations of wine pigments were stymied during that era. The question of their identity was a major challenge for wine chemists. A number of techniques showed that the pigments were polymeric in nature. Some structures were postulated by mid-century based on reactions between anthocyanins and condensed tannin, and later postulated wine pigments were observed in model reactions. Some related compounds were then observed in wine. By the end of the 20th century, the ionization of non-volatiles for mass spectrometry opened the door to these compounds. In addition, a new class of compounds was observed, the pyranoanthocyanins, a product of fermentation and aging metabolites with anthocyanins. These compounds possess the pigment stability to SO₂ and pH change that is characteristic of aged red wine. Aging experiments show a dynamic situation with shifts in the population of pigment classes over time. The very large number of diverse pigments explains why it has been so difficult to answer the century-old question of the structure of wine pigments. Our current understanding is founded on the use of mass spectral analysis using electrospray and related ionization techniques over the last 25 years. Future progress will rely on more sophisticated analysis of this very complex mixture of substances. © 2019 Society of Chemical Industry     

Optimal Guaranteed Cost Tracking of Uncertain Nonlinear Systems Using Adaptive Dynamic Programming with Concurrent Learning

In this paper, based on adaptive dynamic programming (ADP) with concurrent learning, the problem of optimal guaranteed cost tracking is studied for a class     

改善硫精矿浓密机溢流跑浑试验研究

本文旨在改善某选厂硫精矿浓密机溢流跑浑问题,对生产现场进行勘察和分析,分析浓密机溢流跑浑的原因,并开展原矿配比和沉降试验研究。对采场原矿矿样和硫精矿矿浆进行系统的试验研究,分别采用不同沉降方案进行条件试验,考察絮凝剂种类、絮凝剂用量、pH调整剂用量、不同药剂之间的配比等条件对沉降的影响,确定合适的原矿配比及合理药剂制度,有效地控制金属在溢流中的损失,充分获取现有产品的蕴含价值。