The detection and treatment of increasing air pollution due to technological developments represent some of the most important challenges facing the world today. Indeed, there has been a significant increase in levels of environmental pollution in recent years. The aim of the work presented herein is to design an intelligent predictor for the concentrations of air pollutants over the next 2 days based on deep learning techniques using a recurrent neural network (RNN). The best structure for its operation is then determined using a particle swarm optimization (PSO) algorithm. The new predictor based on intelligent computation relying on unsupervised learning, i.e., long short-term memory (LSTM) and optimization (i.e., PSO), is called the smart air quality prediction model (SAQPM). The main goal is to predict six the concentrations of six types of air pollution, viz. PM2.5 particulate matter, PM10, particulate matter, nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and sulfur dioxide (SO2). SAQPM consists of four stages. The first stage involves data collection from multiple stations (35 in this case). The second stage involves preprocessing of the data, including (a) separation of each station with an independent focus, (b) handle missing values, and (c) normalization of the dataset to the range of (0, 1) using the MinMaxScalar method. The third stage relates to building the predictor based on the LSTM method by identifying the best structure and parameter values (weight, bias, number of hidden layers, number of nodes in each hidden layer, and activation function) for the network using the functional PSO algorithm to achieve a goal. Thereafter, the dataset is split into training and testing parts based on the ten cross-validation principle. The training dataset is then used to build the predictor. In the fourth stage, evaluation results for each station are obtained by reading the concentration of each pollutant each hour for at most 30 days then taking the average of the symmetric mean absolute percentage error (SMAPE) for 25 days only.

A new method for prediction of air pollution based on intelligent computation

Superlubricity has been developing very rapidly in recent years as a new and important area in tribology. Many new phenomena and materials, as well as some new mechanisms in both liquid and solid superlubricity have been obtained. In liquid superlubricity, tens of new kinds of liquids with superlubricity have been found (e.g., water-based liquids, oil-based lubricants, and liquids combined with additives of two-dimensional (2D) materials that exhibit very good superlubricity properties under high pressure). In the field of solid superlubricity, more materials with superlubricity have been observed, including graphene-to-graphene surfaces, highly oriented pyrolytic graphite to graphene surfaces, and heterostructure surfaces where a friction coefficient as low as 0.00004 has been obtained. However, superlubricity is still under laboratory research. What is the future of superlubricity? What is the barrier restricting superlubricity from industrial applications? How do we transfer superlubricity from scientific research to industrial application? These questions and application fields of superlubricity in near future have been analyzed, and the concept of “superlubricitive engineering” has been proposed in the present work.

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Superlubricitive engineering—Future industry nearly getting rid of wear and frictional energy consumption

An impedance controller for industrial manipulators is presented in this paper Special attention has been paid to all the aspects that qualify an industrial robot, including decentralized proportional-integral-derivative position control, torsional flexibility, and friction at the joints A discussion of a single-degree-of-freedom (DOF) case is first presented The selection of the impedance parameters is based on the behavior in contact and makes reference to a new design parameter, the compliance bandwidth The single-DOF analysis is then used in the design of the impedance controller for a complete manipulator A rotational impedance based on a geometrically consistent representation of the orientation is used Several experimental results obtained on a 6-DOF industrial robot, equipped with a force/torque sensor, are presented The experiments show the effectiveness of the proposed approach in several conditions, including contact with an extremely stiff surface and noncontact/contact transition

Impedance control for elastic joints industrial manipulators.

Dynamics analysis of planar rigid-flexible coupling deployable solar array system with multiple revolute clearance joints

A general methodology to establish the contact force model for complex contacting surfaces

Dynamics modeling and control of a 6-DOF space robot with flexible panels for capturing a free floating target

It is well known that space robots play a significant role in the human space activities. Capturing a free floating object in space is one of important missions assigned to space robots and it has increasingly attracted researchers’ attention recently. In this paper, the dynamics and control of capturing a floating rigid body using a space robot are investigated. The dynamic model of the system is established by the single direction recursive construction method and the Jourdain’s velocity variation principle. The contact force between space robots and targets has been set up based on the Hertz contact theory. Then the influence on the whole system incurred by this contact force has been thoroughly analyzed through simulations of both central and eccentric impact. Our simulation result verified the impact on the whole system caused by the contact force, and it also indicated the extreme complexity of the dynamic response caused by impact during the capture process. The space robot base attitude has been controlled using the controller based on the nonlinear decoupling method. Our simulation results showed adequate effectiveness.

Xiao-Feng Liu

Papers

Dynamics modeling and control of a 6-DOF space robot with flexible panels for capturing a free floating target

Dynamics and control of capture of a floating rigid body by a spacecraft robotic arm

Dynamics and control of space robot considering joint friction

Dynamics analysis of flexible space robot with joint friction

Deployment dynamics and control of large-scale flexible solar array system with deployable mast