Search

Sliding mode control (SMC) is a widely used control law for quadrotor regulation and tracking control problems. The purpose of this article is to solve the tracking problem of quadrotors using a relatively novel nonlinear control law based on SMC that makes use of a conditional integrator. It is demonstrated by a motivation example that the proposed control law can improve the transient response and chattering shortcomings of the previous approaches of similar SMC based controllers. The adopted Newton–Euler model of quadrotor dynamics and controller design is treated separately in two subsystems: attitude and position control loops. The stability of the control technique is demonstrated by Lyapunov's analysis and the effectiveness and performance of the proposed method are compared with a similar integral law, also based on SMC, and validated by tracking control problems using numerical simulations. Simulations were developed in the presence of external disturbances in order to evaluate the controller robustness. The effectiveness of the proposed controller was verified by performance indexes, demonstrating less accumulated tracking errors and control activity and improvement in the transient response and disturbance rejection when compared to a conventional integrator sliding mode controller. [ABSTRACT FROM AUTHOR]

An inverse problem of damage identification and localization in a structure is modelled as a robust optimization problem. In the robust optimization problem, the optimum value and small variations around this optimum value are considered. The structural health monitoring damage detection problem is solved using a multiobjective genetic algorithm. So, the robust optimum value is obtained by solving a multiobjective problem where a functional and a variance function of this functional are used. This variance function is obtained by a Design of Experiment with regression and also through a relation between functional variance and damage parameters found by artificial neural network. As a multiobjective genetic algorithm obtains multiple solutions, a fuzzy decision making technique finds the better tradeoff solution for the problem. Boundary element method is utilized to obtain the distribution of stress to elastostatic problem. Numerical results clearly show that the proposed strategy and the use an optimized fuzzy decision making results in accurate damage identification and represents a powerful tool for structural health monitoring. Based on the analysis and numerical results, suggestions to potential researchers have also been provided for future scopes. [ABSTRACT FROM AUTHOR]

The performance and behavior of composite structures can be significantly affected by degradation and damage. Degradation can be caused by exposure to environmental conditions and damage can be caused by handling conditions, such as impact and loading. Such damages are not always visible on the surface and could potentially lead to catastrophic structural failures. This paper addresses the specific challenge of using numerical simulations to assess damage detection techniques applied to composite laminated plates. This study aims to solve the direct and inverse problem of damage detection by combining numerical and experimental data. Finite element analysis was carried out to analyze the direct problem of mechanical response. Heuristic optimization techniques were used to solve the direct and inverse problem by combining data from a model with that of the experiment to identify structural damage. This study also sought to update the finite element model by minimizing the objective function. The structure studied was constituted of a composite plate. Two damage models were used: (i) circular hole and (ii) delamination (local stiffness reduction). The results of the optimization algorithms show good efficacy in the detection of structural damage, identifying the damaged location on the structure and also quantifying the size of the damage in real composite structures. A method has been proposed to identify the damage in CFRP plates using remote vibration measurements. Furthermore, the numerical simulation and experimental tests have been used to verify the method. [ABSTRACT FROM AUTHOR]

AbstractThis paper presents an analysis of a sandwich structure featuring an auxetic core, manufactured through Vacuum Assisted Resin Transfer Molding (VARTM) using carbon-aramid hybrid fibers. The core was 3D printed with polylactic acid (PLA). Experimental testing of the structure provided results for validating a cost-effective numerical model. The response surface methodology identified results for different sandwich panel configurations, revealing that auxetic behavior depends on the core’s adopted configuration. Increasing the fiber-core contact area induces auxetic behaviors. The structure underwent optimization using the Lichtenberg algorithm, yielding models with 40.32% higher failure load, 36.36% higher natural frequency, and over 20% mass reduction. [ABSTRACT FROM AUTHOR]