Design of Adaptive Fuzzy PID Altitude Control System for Unmanned Aerial Vehicle

Based on Matlab/Simulink and Fuzzy Logic toolboxes, the altitude control system is designed and simulated. The validity of conventional PID control method and adaptive fuzzy PID control method is compared. It can be drawn out that the adaptive fuzzy PID control method is superior to the conventional PID in rising time and overshoot etc. The effectiveness of a fuzzy PID controller shows potential application in the future, especially in the presence of model uncertainty or changing dynamics and time-varying parameters.

More Detailed Disturbance Measurement and Active Disturbance Rejection Altitude Control for a Flapping Wing Robot Under Internal and External Disturbances

With the goal of designing a biologically inspired robot that can hold a stable hover under internal and external disturbances.We designed a tailless Flapping-wing Micro Aerial Vehicle(FMAV)with onboard 3D velocity perception.In this way,the wind disturbance caused by the relative motion of the FMAV can be quantified in real time based on the established altitudinal dynamics model.For the rest of the total disturbance,an active disturbance rejection controller is proposed to estimate and suppress those disturbances.In comparison with the traditional PID controller,this proposed approach has been validated.The results show that,in the hovering flight with the internal unmodeled dynamics,the root-mean-square of height controlled is only 2.53 cm.Even with the different weights of loads mounting on the FMAV,the ascending trajectory of flights remains impressively consistent.In the forward flight with the external disturbance,the root-mean-square error of height controlled is 2.78 cm.When the FMAV flies over a ladder introducing an abrupt external disturbance,the maximum overshoot is only half of that controlled by the PID controller.To our best knowledge,this is the first demonstration of FMAVs with the capability of sensing motion-generated wind disturbance onboard and handling the internal and external disturbances in hover flight.

Design of an Executable ANFIS-based Control System to Improve the Attitude and Altitude Performances of a Quadcopter Drone

Nowadays,quadcopters are presented in many life applications which require the performance of automatic takeoff,trajectory tracking,and automatic landing.Thus,researchers are aiming to enhance the performance of these vehicles through low-cost sensing solutions and the design of executable and robust control techniques.Due to high nonlinearities,strong couplings and under-actuation,the control design process of a quadcopter is a rather challenging task.Therefore,the main objective of this work is demonstrated through two main aspects.The first is the design of an adaptive neuro-fuzzy inference system(ANFIS)controller to develop the attitude and altitude of a quadcopter.The second is to create a systematic framework for implementing flight controllers in embedded systems.A suitable model of the quadcopter is also developed by taking into account aerodynamics effects.To show the effectiveness of the ANFIS approach,the performance of a well-trained ANFIS controller is compared to a classical proportional-derivative(PD)controller and a properly tuned fuzzy logic controller.The controllers are compared and tested under several different flight conditions including the capability to reject external disturbances.In the first stage,performance evaluation takes place in a nonlinear simulation environment.Then,the ANFIS-based controllers alongside attitude and position estimators,and precision landing algorithms are implemented for executions in a real-time autopilot.In precision landing systems,an IR-camera is used to detect an IR-beacon on the ground for precise positioning.Several flight tests of a quadcopter are conducted for results validation.Both simulations and experiments demonstrated superior results for quadcopter stability in different flight scenarios.

Robust control for an unmanned helicopter with constrained flapping dynamics

In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints. For handling the state constraints, the barrier Lyapunov function and the saturation function are employed. And, the prescribed performance method is used to deal with the flapping angle constraints for the unmanned helicopter. It is proved that the proposed control approach can ensure that all the signals of the resulting closed-loop system are bounded, and the tracking errors are within the prescribed performance bounds for all time. The numerical simulation is given to illustrate the performance of the proposed scheme.

Passive attitude stabilization of ionic-wind-powered micro air vehicles

The ionic-wind-powered Micro Air Vehicles(MAVs)can achieve a higher thrust-toweight ratio than other MAVs.However,this kind of MAV has not yet achieved controlled flight because of the unstable thrust produced by the ionic wind and the dynamic instability related to the small size.In this paper,a passive attitude stabilization method of the ionic-wind-powered MAV using air dampers is introduced.The key factors that influence the performance of the air dampers,including the layout,position,and area of the air dampers,are theoretically studied.The appropriate optimal position of the air dampers is also obtained by Monte Carlo stochastic simulations.Then the proposed passive attitude stabilization method is applied to the ionic-wind-powered MAVs of different wingspan(2 cm and 6.3 cm).Finally,the experimental results show that using the proposed method,attitude stabilization is achieved for the first time for the ionic-wind-powered MAV.Moreover,the altitude control of an ionic-wind-powered MAV with a wingspan of 6.3 cm is also demonstrated.