A direct adaptive controller for EAF electrode regulator system using neural networks

This paper proposes a robust adaptive neural network controller (RANNC) for electrode regulator system. According to the characteristics of electrode regulator system, an affine-like equivalent model is first derived. Then, the nonlinear control law is derived directly based on the affine-like equivalent model identified with neural networks, which avoids complex control development and intensive computation. The control scheme is simple enough that it can be implemented on an automotive microcontroller system, and the performance meets the system requirements. The stability of the system is established by the Lyapunov method. Several simulations illustrate the effectiveness of the controller.

https://downloads.hindawi.com/journals/mpe/2013/874890.pdf

NN-Based Approximate Model Control for the EAF Electrode Regulator System

Multicomponent lead compounds, including lead (Pb), lead oxide (PbO), lead dioxide (PbO2), and lead sulfate (PbSO4), in spent lead–acid batteries (LABs), if not properly disposed of and recycled, will cause serious pollution and damage to the ecological environment. Pyrometallurgical smelting performed above 1000 °C often incurs high energy consumption and lead pollution. In this study, a low-temperature (300 °C), oxygen-free roasting process was proposed. With potassium bisulfate (KHSO4) as the roasting reagent, the uniform conversion of multicomponent lead compounds from spent lead paste (SLP) to PbSO4 was successfully realized in one step. We observed that PbO2 species were relatively chemically stable, during the oxygen-free roasting. However, the decomposition of PbO2 into PbO can be achieved by heating to 300 °C, resulting in an effective conversion to PbSO4. The optimal conditions for PbSO4 production were a heating temperature of 300 °C, an SLP/KHSO4 mass ratio of 1:1, and a holding time of 10.0 min. Life cycle assessment results show that the recycling of 1.0 t spent LABs can reduce carbon emissions of 2.45 t CO2 and smog of 0.13 t. Our research provides an emission-free, low-temperature, and negative-carbon strategy for facile and cost-effective recycling of spent LABs, as an alternative to traditional pyrometallurgical smelting. 

Batch Production of Lead Sulfate from Spent Lead–Acid Batteries via an Oxygen-Free Roasting Route: A Negative-Carbon Strategy

The approaches of motivating people for the collection of electronic waste (e-waste) are often insufficient due to inadequate methods of given incentives. Prior research studies have been carried out to tackle the issue of e-waste management in a broad sense. The findings of those studies indicated diverse strategies, each of which is relevant solely to a restricted range of electronic e-waste reprocessing circumstances. The current study has presented a proposed technique for incentivizing tasks and activities associated with the collection of e-waste through the adoption of the vector space technique. The method this research undertakes lies with utilizing blockchain smart contract technology. The reason for selecting this approach lies with the mapping of tasks, the nature of activities, and their magnitude, in order to derived an incentive. While the vector space model defines the set of tasks with their corresponding incentives, blockchain smart contract maps them together and establishes them in a record. Experimental scenarios for the calculation of incentives are presented; the findings reveal that among many scenarios of allocating incentives for e-waste collection, the best case is by utilizing a weighting scale scheme where each task and activity is mapped to its associated incentive rather than providing fixed incentive values. Ethereum was used as a digital token for each unit of incentive. This concept has contributed in encouraging personal accountability in the management of e-waste collection in order to cultivate sustainable behaviors for a long-term solution.

/pdf/electronic-waste-collection-incentivization-scheme-based-on-30znnpnj.pdf

Electronic Waste Collection Incentivization Scheme Based on the Blockchain

Towards electrode control system of LF furnace, a adaptive inverse control algorithm based on RBF NN is presented, which identifies real-time and decoupling by RBF NN on-line, and designs a computer control system based on control software of WinAC. The results of application show that this system is able to adapt with load change and external interference very well, and could overcome the dithering of electrode effectively, especially The control system have a good tacking characteristic.

Kun Li

Papers

Application of the Electrode System Intelligent Controller for Ladle Furnace

Upgrading waste electrical and electronic equipment recycling through extended producer responsibility: A case study of GEM CoLtd.