This paper presents a novel speed estimator using Reactive Power based Model Reference Neural Learning Adaptive System (RP-MRNLAS) for sensorless indirect vector controlled induction motor drives. The Model Reference Adaptive System (MRAS) based speed estimator using simplified reactive power equations is one of the speed estimation method used for sensor-less indirect vector controlled induction motor drives. The conventional MRAS speed estimator uses PI controller for adaptation mechanism. The nonlinear mapping capability of Neural Network (NN) and the powerful learning algorithms have increased the applications of NN in power electronics and drives. This paper proposes the use of neural learning algorithm for adaptation in a reactive power technique based MRAS for speed estimation. The proposed scheme combines the advantages of simplified reactive power technique and the capability of neural learning algorithm to form a scheme named “Reactive Power based Model Reference Neural Learning Adaptive System” (RP-MRNLAS) for speed estimator in Sensorless Indirect Vector Controlled Induction Motor Drives. The proposed RP-MRNLAS is compared in terms of accuracy, integrator drift problems and stator resistance versions with the commonly used Rotor Flux based MRNLAS (RF-MRNLAS) for the same system and validated through Matlab/Simulink. The superiority of the RP-MRNLAS technique is demonstrated.

The aim of the study described herein was to design, construct and test a demonstrator of a system to control the direction of the resultant thrust vector of a rocket motor to be used in short range anti-tank missiles with a mass of up to 15 kg. The novelty of the system is that the direction of the resultant thrust vector is manipulated by means of moveable jet vanes integrated with a moveable nozzle diffuser through telescopic connectors. The technology demonstrator was built using different materials and different manufacturing processes. The first versions were 3D printed from plastic materials. Minor modifications to the design were made at an early stage. The final version had the main components made of aluminum using CNC machining. The system, with and without jet vanes, was tested on a specially developed test rig equipped with a multi-axis sensor to measure forces and torques. The nozzle performance parameters measured and analyzed in this study were the components of the thrust vector, the moments and the effective vectoring angle. The findings show that the experimental data are in good agreement with the results of earlier simulations and that the demonstrator is fully operational.

This article discusses the most important issues regarding the implementation of digital algorithms for control and drive technology in industrial machines, especially in open mining machines. The article presents the results of tests in which the algorithm and drive control parameter settings were not selected appropriately for voltage-fed induction motors, and where the control speed was not verified by any of the available motoring or simulation methods. We then show how the results can be improved using field-oriented control algorithms and deep parameters analysis for sensorless field-oriented performance.

The paper proposes a newrobust fuzzy gain adaptation of the sliding mode (SMC) power control strategy for the wind energy conversion system (WECS), based on a doubly fed induction generator (DFIG), to maximize the power extracted from the wind turbine (WT). The sliding mode controller can deal with any wind speed, ingrained nonlinearities in the system, external disturbances and model uncertainties, yet the chattering phenomenon that characterizes classical SMC can be destructive. This problem is suitably lessened by adopting adaptive fuzzy-SMC. For this proposed approach, the adaptive switching gains are adjusted by a supervisory fuzzy logic system, so the chattering impact is avoided. Moreover, the vector control of the DFIG as well as the presented one have been used to achieve the control of reactive and active power of the WECS to make the wind turbine adaptable to diverse constraints. Several numerical simulations are performed to assess the performance of the proposed control scheme. The results show robustness against parameter variations, excellent response characteristics with a reduced chattering phenomenon as compared with classical SMC.