aiop v2.0 uav 433mhz autopilot gps flight control system

AIOP V2.0 UAV 433MHZ AUTOPILOT GPS FLIGHT CONTROL SYSTEM PLUS

The UAV's tracking results along the desired trajectory are apt to have a certain static error. are smaller and, the above-mentioned non-linear guidance controller is equivalent to a PD. When following a straight line, the navigation deviation D and heading angle deviation η. Time domain system identification methods were used to obtain a simple auto-regressive model of the UAV roll-channel with exogenous input to operate under conditions of wind gusts and payload variations. focused on the design and implementation of a roll-channel fractional order proportional integral (PI λ) flight controller for a small fixed-wing UAV.

AIOP V2.0 UAV 433MHZ AUTOPILOT GPS FLIGHT CONTROL SYSTEM PLUS

Luo developed a fractional order (PI) λ controller to improve the flight control performance and robustness of a small fixed-wing UAV the inner closed-loop system of the roll-channel is approximately identified as a first-order plus time delay model using flight test data. He also proposed designing heading and air speed control commands to accomplish the constrained nonlinear tracking control for small fixed-wing UAVs. Ren considered the problem of constrained non-linear trajectory tracking control to reduce the twelve-state UAV model to a six-state model with altitude, heading, and velocity command inputs. implemented lateral path-following based on the proportional-integral-derivative (PID) feedback method in simulation. According to the criterion of minimum energy and minimum manoeuvring, Zhu et al. In complicated flight terrain, non-linear path-following is also required to perform special tasks and improve flying quality.Ī number of trajectory planning and control techniques have been extensively studied for UAVs. The navigation system is the major subsystem of a UAV, as it provides the rest of the subsystems with pre-defined position, velocity and attitude information in order to control the aircraft, manage the mission or inform the pilot. Generally, people use UAVs in aerial photography and surveillance, which require steady path-following properties. The UAV market for both military and civilian applications has grown rapidly. With a short wingspan and light weight, small fixed-wing UAVs can be built easily operated by only one or two persons and can be carried and launched by hand. In recent years, small fixed-wing unmanned aerial vehicles (UAVs) have been attracting more and more interest, since they are portable, expendable and manoeuvrable. Flight tests and survey missions were carried out with our self-developed delta fixed-wing UAV and MEMS-based autopilot to confirm the effectiveness and practicality of the proposed navigation method. The non-linear controller can automatically adapt to ground velocity change, which is usually caused by gust disturbance, thus the UAV has good wind resistance characteristics. The longitudinal control employs traditional linear PID feedback to achieve the desired altitude of the UAV, while the lateral control uses a non-linear control method to complete the desired trajectory. The three-dimensional (3D) trajectory tracking control of a UAV could be approximately divided into lateral control and longitudinal control.

The proportional-integral-derivative (PID) control was adopted for stabilization and attitude control.

The trajectory tracking navigation loop is the outer loop of the attitude loop, while the attitude control loop is the outer loop of the stabilization loop. The system is designed under the inner loop and outer loop strategy. This paper presents a flight control and navigation system for a fixed-wing unmanned aerial vehicle (UAV) with low-cost micro-electro-mechanical system (MEMS) sensors.

Aiop v2.0 uav 433mhz autopilot gps flight control system