This paper discusses the integration of health monitoring and flight control systems for small Unmanned Aerial Vehicles (UAVs). After briefly reviewing previous fuzzy logic controllers (FLC) of air vehicles, a very low cost integration method is proposed. The proposed fuzzy logic (FL) selects the best gain values for the operation of PD or PID controllers of the autonomous flight system accordi...

This paper presents a methodology to integrate a fuzzy coprocessor described in VHDL (VHSIC Hardware Description Language) to a soft processor embedded into an FPGA, which increases the throughput of the whole system, since the controller uses parallelism at the circuitry level for high-speed-demanding applications, the rest of the application can be written in C/C++. We used the ARM 32-bit sof...

In this paper, we present an effective and efficient diagnosis system based on particle swarm optimization (PSO) enhanced fuzzy k-nearest neighbor (FKNN) for Parkinson’s disease (PD) diagnosis. In the proposed system, named PSO–FKNN, both the continuous version and binary version of PSO were used to perform the parameter optimization and feature selection simultaneously. On the one hand, the ne...

The paper presents a comparative study regarding the control (using an adaptive neuro-fuzzy controller and a PD controller) based on the simulation of wind energy conversion systems functioning. There are considered several simulations based on asynchronous generator usage, by using the dedicated MATLAB-PSB (Power System Blockset) toolbox implementations.

In this paper, we present a novel method based on active contours for segmentation and fuzzy rule based classification of microscopic images of esophagus tissues obtained from the abnormal regions of human esophagus detected through endoscopy. This method is used for classification of Squamous Cell Carcinoma (SCC) of esophagus, namely, well differentiated (WD), moderately differentiated (MD), a...

A new high-resolution direction of arrival (DOA) estimation technique using a neural fuzzy network based on phase difference (PD) is proposed in this paper. The conventional DOA estimation method such as MUSIC and MLE, are computationally intensive and difficult to implement in real time. To attach these problems, neural networks have become popular for DOA estimation in recent years. However, ...

In this paper, a novel Model Reference Adaptive Control (MRAC)-based hybrid control algorithm is presented for the trajectory tracking of a tri-rotor Unmanned Aerial Vehicle (UAV). The mathematical model of the tri-rotor is based on the Newton–Euler formula, whereas the MRAC-based hybrid controller consists of Fuzzy Proportional Integral Derivative (F-PID) and Fuzzy Proportional Derivative (F-P...

Simple conventional control methods, such as PD and PID controllers, are widely used in industrial applications. Such controllers exhibit poor performance when applied to systems containing nonlinearities arising from unknown deadzones. In this report, we propose a novel fuzzy logic-based precompensation approach for controlling systems with deadzones. The control structure consists of a fuzzy ...

Light-weight flexible arms will most likely constitute the next generation robots due to their large payload carrying capacities at high speeds and less power demand. Control problem of robots with flexible members is more complex compared to rigid robots due to vibrations during the motion. This paper presents the social foraging behavior of Escherichia coli bacteria to optimize hybrid Fuzzy P...

This paper presents the application of an adaptive fuzzy logic controller with feed-forward component (AFLCF) to the Selective Compliance Assembly Robot Arm (SCARA Robot). The feed forward torque component is computed on-line using an artificial neural network (ANN) which has been trained off-line. This feed-forward component is designed to deliver the ideal torque component to the robot derive...