This paper aims to present data analysis of quadcopter dynamic attitude on a circular trajectory, specifically by comparing the modeling results of conventional Proportional Integral Derivative (PID) and Fuzzy-PID controllers. Simulations of attitude stability with both control systems were done using Simulink toolbox from Matlab so the identification of each control system is clearly seen. Each control system algorithm related to roll and pitch angles which affects the horizontal movement on a circular trajectory is explained in detail. The outcome of each tuning variable of both control systems on the output movement is observable while the error magnitude can be compared with the reference angles. To obtain a deeper analysis, wind disturbance on each axis was added to the model, thus differences between each control system are more recognizable. According to simulation results, the Fuzzy-PID controller has relatively smaller errors than the PID controller and has a better capability to reject disturbances. The scaling factors of gain values of the two controllers also play a vital role in their design.

Non-linear dynamic movement of quadcopter was analyzed using position tracking method in a circular trajectory. The result was used to obtain control system algorithm which can enhance maneuver ability. The control system was modelled into feedback linearization and LQR (Linear Quadratic Regulator) controller, both were used to stabilize quadcopter attitude in the trajectory. Quadcopter behavior while using feedback linearization modeling and LQR control were clearly seen in pitch-roll position in circular trajectory and at the time of bounded disturbance. Wind parameter appraisal was added to boost the robustness. To get optimal result, overall control system was tuned with PID (Proportional Integral Derivative) loop control. The study showed that adjustment of the weight variable on LQR and coefficient on PID resulted in better stability and performance of quadcopter dynamic movement. Overall, control algorithm for modeling had the capability to reject disturbance although small error still occurred in the output trajectories tracking.

This study presents a detailed analysis of an air monitoring development system using quadcopters. The data collecting method is based on gas dispersion investigation to pinpoint the gas source location and determine the gas concentration level. Due to its flexibility and low cost, a quadcopter was integrated with air monitoring sensors to collect the required data. The analysis started with the sensor placement on the quadcopter and their correlation with the generated vortex. The reliability and response time of the sensor used determine the duration of the data collection process. The dynamic nature of the environment makes the technique of air monitoring of topmost concern. The pattern method has been adapted to the data collection process in which area scanning was marked using a point of interest or grid point. The experiments were done by manipulating a carbon monoxide (CO) source, with data readings being made in two ways: point source with eight sampling points arranged in a square pattern, and non-point source with 24 sampling points in a grid pattern. The quadcopter collected data while in a hover state with 10 s sampling times at each point. The analysis of variance method (ANOVA) was also used as the statistical algorithm to analyze the vector of gas dispersion. In order to tackle the uncertainty of wind, a bivariate Gaussian kernel analysis was used to get an estimation of the gas source area. The result showed that the grid pattern measurement was useful in obtaining more accurate data of the gas source location and the gas concentration. The vortex field generated by the propeller was used to speed up the accumulation of the gas particles to the sensor. The dynamic nature of the wind caused the gas flow vector to change constantly. Thus, more sampling points were preferred, to improve the accuracy of the gas source location prediction.

Robotic exoskeletons are a trending topic in both robotics and rehabilitation therapy. The research presented in this paper is a summary of robotic exoskeleton development and testing for a human hand, having application in motor rehabilitation treatment. The mechanical design of the robotic hand exoskeleton implements a novel asymmetric underactuated system and takes into consideration a number of advantages and disadvantages that arose in the literature in previous mechanical design, regarding hand exoskeleton design and also aspects related to the symmetric and asymmetric geometry and behavior of the biological hand. The technology used for the manufacturing and prototyping of the mechanical design is 3D printing. A comprehensive study of the exoskeleton has been done with and without the wearer’s hand in the exoskeleton, where multiple feedback sources are used to determine symmetric and asymmetric behaviors related to torque, position, trajectory, and laws of motion. Observations collected during the experimental testing proved to be valuable information in the field of augmenting the human body with robotic devices.

This paper is focused on the dynamic of mathematical modeling, stability, nonlinear gain control by using Genetic algorithm, utilizing MATLAB tool of a quadcopter. Previously many researchers have been work on several linear controllers such as LQ method; sliding mode and classical PID are used to stabilize the Linear Model. Quadcopter has a nonlinear dynamics and unstable system. In order to maintain their stability, we use nonlinear gain controllers; classical PID controller provides linear gain controller rather than nonlinear gain controller; here we are using modified PID control to improve stability and accuracy. The stability is the state of being resistant to any change. The task is to maintain the quadcopter stability by improving the performance of a PID controller in term of time domain specification. The goal of PID controller design is to determine a set of gains: Kp, Ki, and Kd, so as to improve the transient response and steady state response of a system as: by reducing the overshoot; by shortening the settling time; by decrease the rise time of the system. Modified PID is the combination of classical PID in addition to Genetic Algorithm. Genetic algorithm consists of three steps: selection, crossover, and mutation. By using Genetic algorithm we correct the behavior of quadcopter.

An unbalanced propeller can affect a quadcopter’s performance due to vibration, also decreasing its thrust’s yield. Analyses were conducted to determine the correlation between vibration in the dynamic movement of a balanced and an imbalanced propeller using a laser vibrometer (portable digital vibrometer) PDV-100, to determine the correlation between propeller rotational speed and its vibration, as well as to determine the propeller’s maximum rotational speed to avoid over-vibration. The vibration analysis was conducted on a carbon fiber 2-blade propeller by comparing the results of vibration tests with the propeller blade contour. The vibration response of the propeller has been analyzed at three points, respectively the hub, the center, and the tip of the blade, to determine the point having the largest value of the vibration on the propeller running at a maximum rotation speed of 7000 rpm. The same analysis was made on two propellers: the first one of type 1340 with a diameter of 13 inches and the second one of type 1447 with a diameter of 14 inches. The vibration was reduced by propeller’s static balancing, thus increasing the propeller stability. The result showed that an imbalanced propeller generated a decrease in the rotational speed and higher vibration values compared to the balanced propeller. The vibration values showed a linear dependency to the rotor speed; the higher the speed, the bigger the vibration. The limit of rotational speed for the balanced model of the 1340 type propeller was 5000 rpm whilst the corresponding value for the 1447 type propeller was 4500 rpm. Finally, the result was used to optimize the propeller’s overall performance.