Observer-based adaptive fuzzy control for a class of nonlinear time-delay systems

An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.     

Prediction of phosphorus content of electroless nickel–phosphorous coatings using artificial neural network modeling

A multilayer feedforward neural network with two hidden layers was designed and developed for prediction of the phosphorus content of electroless Ni–P coatings. The input parameters of the network were the pH, metal turnover, and loading of an electroless bath. The output parameter was the phosphorus content of the electroless Ni–P coatings. The temperature and molar rate of the bath were constant ( 91^° \textC, 0.4 \textNi^{\text + +} /\textH₂ \textPO₂ ^{- -} 91^\circ {\text{C}},\:0.4\,{\text{Ni}}^{{{\text{ + + }}}} /{\text{H}}_{2} {\text{PO}}_{2}^{{ - - }} ). The network was trained and tested using the data gathered from our own experiments. The goal of the study was to estimate the accuracy of this type of neural network in prediction of the phosphorus content. The study result shows that this type of network has high accuracy even when the number of hidden neurons is very low. Some comparison between the network’s predictions and own experimental data are given.     

Design, Construction and Calibration of a Triaxial Dynamometer for Measuring Forces and Moments Applied on Tillage Implements in Field Conditions

In this research, a dynamometer was designed, constructed and calibrated to measure the forces and moments applied on tillage implements. This dynamometer is able to measure the three orthogonal forces acting on the implement and the three moments acting around the orthogonal axes, up to a maximum force of 20 kN and a maximum moment of 20 kN m. The dynamometer uses two extended octagonal ring transducers mounted in a back-to-back arrangement with their axes at right angles and has a tubular torque meter for torque measurement. For mechanical design of the dynamometer frame and its units, the finite element method and CATIA software were used. The device was machined from the solid part and high tensile steel. The forces and moments acting on the dynamometer were measured by using the strain gauge bridges on two extended octagonal ring transducers and on the torque meter tube. The results of data analysis, including forces applied on the dynamometer, the designing method of rings and torque meter tubes, the mounting arrangement of load cell parts on each other, the mounting method of load cell on frame and the position of strain gauge on load cell, in other words, the position of different parts of the dynamometer relative to each other has been explained in this paper. Calibration of the measurement unit was done by a calibration system which was designed for static calibration of the triaxial dynamometer. The results of calibration of the measurement unit showed that the designed and constructed dynamometer has appropriate precision, sensitivity and good repeatability for measuring the desired forces and moments. The results showed a high degree of linearity between output voltage of bridges and applied forces and moments. The interaction effects of the applied forces and moments were very negligible.     

Neurotoxicity of Chronic Co-Exposure of Lead and Ionic Liquid in Common Carp: Synergistic or Antagonistic?

Previous studies have indicated that the harmful heavy metal lead (Pb) contamination in aquatic systems has caused intelligence development disorders and nervous system function abnormalities in juveniles due to the increased permeability of the blood–brain barrier. Ionic liquids (ILs) are considered “green” organic solvents that can replace traditional organic solvents. Studies have found the presence of ILs in soil and water due to chemical applications or unintentional leakage. Therefore, what would happen if Pb interacted with ILs in a body of water? Could ILs enable Pb to more easily cross the blood–brain barrier? Therefore, we examined the combined exposure of Pb and ILs in common carp at low concentration (18.3 mg L⁻¹ of Pb(CH₃COO)₂•3 H₂O and 11 mg L⁻¹ of the IL 1-methyl-3-octylimidazolium chloride, 5% of their LC₅₀) for 28 days in the present study. The result of a neurobehavioral assay showed that chronic exposure of lead at lower concentrations significantly altered fish movement and neurobehaviors, indicating that lead exposure caused neurotoxicity in the carp. Increases in the neurotransmitter dopamine levels and injuries in the fish brain accounted for neurobehavioral abnormalities induced by lead exposure. Moreover, we also found that lead could easily cross the blood–brain barrier and caused significant bioaccumulation in the brain. Particularly, our study indicated that the ionic liquid could not synergistically promote blood–brain barrier permeability and hence failed to increase the absorption of lead in the fish brain, suggesting that the combined exposure of lead and ILs was not a synergistic effect but antagonism to the neurotoxicity. The results of this study suggested that ILs could recede the Pb induced neurotoxicity in fish.