New Model Reference Adaptive System Speed Observer for Field-Oriented Control Induction Motor Drives Using Neural Networks

One of the primary advantages of field-oriented controlled induction motor for high performance application is the capability for easy field weakening and the full utilization of voltage and current rating of the inverter to obtain a wide dynamic speed rangeThis paper describes a Model Reference Adaptive System (MRAS) based scheme using Artificial Neural Network (ANN) for online speed estimation of sensorless vector controlled induction motor drive. The proposed MRAS speed observer uses the current model as an adaptive model. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator. The simulation results show good performance in various operating conditions. Also Performance analysis of speed estimator with the change in resistances of stator is presented. Simulation results show this estimator robust to parameter variations especially resistances of stator

Fuzzy Logic Based Direct Power Control of Induction Motor Drive

This paper is the design of an induction motor drive system that can be controlled using direct power control. First the possibilities of direct power control (DPC) of induction motors (IMs) fed by a voltage source inverter have been studied. Principles of this method have been separately evaluated. Also the drive system is more versatile due to its small size and low cost. Therefore it is advantageous to use the system where the speed is estimated by means of a control algorithm instead of measuring. This paper proposed one novel induction motor speed control system with fuzzy logic. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator

The antinociceptive effects of rosuvastatin in chronic constriction injury model of male rats

Introduction: According to studies, statins possess analgesics and anti-inflammatory properties. In the present study, we examined the antinociceptive, anti-inflammatory and antioxidative effects of rosuvastatin in an experimental model of Chronic Constriction Injury (CCI). Methods: Our study was conducted on four groups; sham, CCI (the control group), CCI+rosuvastatin (i.p. 5 mg/kg), and CCI+rosuvastatin (i.p. 10 mg/kg). We performed heat hyperalgesia, cold and mechanical allodynia tests on the 3rd, 7th, 14th, and 21st after inducing CCI. Blood samples were collected to measure the serum levels of Tumor Necrosis Factor (TNF)-α, and Interleukin (IL)-6. Rats' spinal cords were also examined to measure tissue concentration of Malondialdehyde (MDA), Superoxide Dismutase (SOD), and Glutathione Peroxidase (GPx) enzymes. Results: Our findings showed that CCI resulted in significant increase in heat hyperalgesia, cold and mechanical allodynia on the 7th, 14th and 21st day. Rosuvastatin use attenuated the CCI-induced hyperalgesia and allodynia. Rosuvastatin use also resulted in reduction of TNF-α, IL-6, and MDA levels. However, rosuvastatin therapy increased the concentration of SOD and GPx in the CCI+Ros (5 mg/kg) and the CCI+Ros (10 mg/kg) groups compared to the CCI group. Conclusion: Rosuvastatin attenuated the CCI-induced neuropathic pain and inflammation. Thus, antinociceptive effects of rosuvastatin might be channeled through inhibition of inflammatory biomarkers and antioxidant properties