Skip to Main Content
The MAV is very little, so it is easily disturbed by the environment and has week stability. Due to its low Reynolds number, it is easy to be affected by the unstable air (turbulence and gusts), and other outside interference. Recent work in dynamic inversion with neural network may be applied to control a MAV where the reference commands include position, velocity, attitude and angular rate. This control technology can provide the MAV with an admirably command follow and steady control capability. Neural networks are used directly as the controller as well as indirect designs that are based on a neural network process model. The emulator is compiled by using neural network toolbox in MATLAB. Then the main result of this simulation is presented. It indicates that the method has high precision and strong stability, which can serve the control of MAV. Thereafter, an amendment about controlling system with dynamic inversion of the MAV is described.