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The monitoring of wind turbine (WT) systems allows operators to maximize their performance, consequently minimizing untimely shutdowns and related hazard situations while maximizing their efficiency. Indeed, the rational monitoring of WT ensures the identification of the main sources of risks at a proper time, such as internal or external failures, hence leading to an increase in their prevention by limiting the faults' occurrence regarding the different components of wind turbines, achieving production objectives. In this context, the present paper develops a practical monitoring approach using a numerical fault-detection process for the pitch system based on a benchmark wind turbine (WT) model with the main aim of improving safety and security performance. Therefore, the proposed fault-diagnosis procedure deals with eventual faults occurring in the actuators and sensors of the pitch system. In this proposed approach, a simple, logical process is used to generate the correct residuals as fault information based on the redundancy in the actuators and sensors of the pitch sub-systems. The obtained results demonstrate the effectiveness of this proposed process for ensuring the tasks of the fault diagnosis and condition monitoring of the WT systems, and it can be a promising approach for avoiding major damage in such systems, leading to their operational stability and improved reliability and availability. [ABSTRACT FROM AUTHOR]

Due to the essential characteristics and utility of coaxial octocopter vehicles in various real-time applications and many actual domains, this article aims to propose intelligent fuzzy logic controllers (FLC) for a six-degrees-offreedom coaxial octorotor with a dynamic model. Using expert knowledge, the developed control structure is applied to track reference paths in the 3D environment with sufficient stability and effectiveness. The tested octorotor dynamic model is divided into six subsystems: altitude, pitch, roll, yaw, x position, and y position. Meanwhile, a Mamdani fuzzy inference controller is designed and applied for each subsystem to generate the appropriate control action. The simulation and the evolution tasks are done using a MATLAB dynamic model of the controlled process in order to perform and evaluate the proposed intelligent control structures of the 6 DOF octorotor model. The illustrated simulation results demonstrate the designed fuzzy controllers' effectiveness in motion stability and error tracking for different types of paths and all tested variables. [ABSTRACT FROM AUTHOR]

This paper is concerned with a visual navigation method based on type-2 fuzzy logic controllers (T2FLC) and optical flow (OF) approach. A Takagi-Sugeno fuzzy logic controller is used for obstacle avoidance task based on video acquisition and image processing algorithm. To extract information about the environment, the captured image is divided into two parts, the control system uses optical flow values calculated by a Horn-Shunk algorithm to detect and estimate the positions of obstacles. The efficiency of the proposed structure is simulated using Visual Reality Toolbox. The obtained simulation results demonstrate the effectiveness of this autonomous visual navigation system. [ABSTRACT FROM AUTHOR]

Controllers based on fuzzy theory have been applied and implemented in various types of engineering problems, especially in control and robotics. Mobile robot navigation is one of the popular tasks encountered by imprecision and uncertainties and it has been studied using fuzzy logic systems. Type-1 fuzzy system is based on twodimensional fuzzy membership functions. In some applications, this function cannot deal with the resulted uncertainty. Type-2 fuzzy membership function with their imprecise boundaries can give fuzzy sets with membership values instead of a crisp number. The objective of the paper is to use and compare type-1 and type-2 Takagi-Sugeno (TS) fuzzy controllers for mobile robot autonomous navigation. The proposed TS fuzzy controllers are used to infer actions for robot movement based behaviours: goal seeking, obstacle avoidance, and wallfollowing. The simulation results are discussed and compared to show the effectiveness of the designed controllers for robot navigation. [ABSTRACT FROM AUTHOR]