Adaptive neural network control based on neural observer for quadrotor unmanned aerial vehicle

This paper proposes an adaptive neural network control with neural state’s observer for quadrotor. The adaptive approach is used to solve the dynamics uncertainty problem of the controller. To perform the control, a Single Hidden Layer Neural Network (SHLNN) is used. Based on the structure of Sliding Mode Observer (SMO), a new neural observer is proposed to estimate the states. The aim of this work is to propose an observer insensitive to the measurement noise. The stability proof of global system is made by Lyapunov direct method. The adaptation laws of both artificial neural networks (ANNs) are derived from Lyapunov theory. The proposed controller is validated by simulation on the quadrotor under measurement noise conditions. A comparative study with SMO is made to highlight the performances of the proposed neural observer.     

Temperature dependence of elastic strain and damage build-up in He implanted AlN

The elastic strain build-up and damage induced by 50 keV He implantation at RT and 550 °C into (0001)AlN were studied using a combination of XRD experiments, XRD simulation, and TEM experiments. Evidence for strong dynamic annealing with efficient point defect recombination is reported at RT. The point defect recombination is found to be enhanced with increasing implantation temperature where He concentration is low, indicating increased mobility of interstitial-type defects and resulting in low strain. A reversed effect is observed for He concentration exceeding 5 at.% (3 at.%) at RT (550 °C) : thermally activated mechanisms related to the nucleation and growth of He-V complexes overcome the point defect recombination and promote the strain and damage build-up. At 1 × 10¹⁷ cm^?2, only clusters of interstitials are observed at RT, whilst bubbles and basal stacking faults are additionally formed at 550 °C for a critical He concentration estimated to be close to 4–6 at.%.     

Line-to-line Voltage Space Vector Modulation for Neutral-point Clamped Multi-level Converter with DC-link Capacitor Voltage Balancing Using Redundant Vectors

This article presents space vector modulation of line-to-line voltage for the three-phase neutral-point clamped n-level converter with DC-link capacitor voltage balancing using redundant vectors. The developed modulation strategy is based on an equivalent matrix structure of the neutral-point clamped n-level converter. The relation between the 3 × (n – 1) switching functions of the matrix converter and gate signals of transistors of the neutral-point clamped n-level converter is given. A line-to-line space vector modulation strategy for a matrix inverter is used to obtain the switching function. For one switching function, there is more than one combination to produce each output voltage. Thus, redundancies of different switch configurations for generation of intermediate voltages are used to limit the deviation of capacitor voltages. The gate signals of the neutral-point clamped n-level converter can be calculated by inversing the modeling parts. Here, line-to-line voltage space vector modulation for a neutral-point clamped n-level converter is designed without using a Parks transform. Moreover, n × (n – 1) redundant vectors are used for DC bus voltage balancing. To highlight the performances of the developed modulation strategy, simulation results are given for five- and seven-level neutral-point clamped converters. Experimental results are given for a neutral-point clamped three-level converter.     

Observer-based Adaptive Fuzzy Backstepping Tracking Control of Quadrotor Unmanned Aerial Vehicle Powered by Li-ion Battery

In this paper, an Adaptive Fuzzy Backstepping Control (AFBC) approach with state observer is developed. This approach is used to overcome the problem of trajectory tracking for a Quadrotor Unmanned Aerial Vehicle (QUAV) under wind gust conditions and parametric uncertainties. An adaptive fuzzy controller is directly used to approximate an unknown nonlinear backstepping controller which is based on the exact model of the QUAV. Besides, a state observer is constructed to estimate the states. The stability analysis of the whole system is proved using Lyapunov direct method. Uniformly Ultimately Bounded (UUB) stability of all signals in the closed-loop system is ensured. The proposed control method guarantees the tracking of a desired trajectory, attenuates the effect of external disturbances such as wind gust, and solves the problem of unavailable states for measurement. Extended simulation studies are presented to highlight the efficiency of the proposed AFBC scheme.     

DC Link Capacitor Voltage Balancing in a Three-Phase Diode Clamped Inverter Controlled by a Direct Space Vector of Line-to-Line Voltages

In this paper, the direct modulation strategy of a three-level inverter with self stabilization of the dc link voltage is extended to a five-level inverter. Therefore, a new modeling and control strategy of a five-level three-phase diode-clamped inverter (DCI) is presented. The obtained modeling shows that modulated multilevel voltages are obtained by combination of eight different three-level functions, which are called modulation functions. Therefore, a space-vector scheme without using a Park transform is explained. Based on this algorithm, the location of the reference voltage vector can be easily determined. Then, the voltage vectors are selected to generate corresponding levels and simultaneously their durations are calculated. More over, the redundancies of different switch configurations for the generation of intermediate voltages are used to limit the deviation of capacitor voltages. Experimental results are given to illustrate the proposed control strategy of the three-phase three-level diode clamped inverter. Then, obtained results for a five-level three-phase DCI with the extended version of the control strategy are presented to show the good performances of the proposed balancing modulation.