A quadrotor attitude control method based on a T-S fuzzy model

Abstract

The invention discloses a quadrotor attitude control method based on a T-S fuzzy model. According to the invention, a T-S fuzzy model is derived by a simplified attitude dynamic equation; a fuzzy state feedback controller is designed by using a parallel step-by-step compensation technique; while the deviation between the simplified model and an actual model is compensated, stable control of an attitude angle of a quadcopter is realized. According to the invention, compared with a quadcopter attitude dynamical system having strong nonlinearity and strong coupling performance, a more reasonable simplified model is brought forward; the simplified model derived from small angle assumption carried out only on roll angles is more accurate than the model derived from small angle assumption carried out both on the roll angles and pitch angles simultaneously; the model deviation in designing of a controller can be reduced as much as possible; the whole control structure is relatively simple; the calculating efficiency is high; and the convergence speed is fast.

Description

Technical field [0001] The invention belongs to the technical field of unmanned aerial vehicles, and specifically relates to a four-rotor attitude control method based on a T-S fuzzy model. Background technique [0002] With the rapid development of embedded processing chips and sensor chips, small drones have been widely used in both military and civilian fields. Among these UAVs, the rotary wing UAV has attracted the attention of many UAV companies and scientific research institutions because of its vertical take-off, landing and hovering characteristics. At present, rotary-wing UAVs have been widely used in film and television aerial photography, power lines and oil pipeline inspections, anti-drug inspections, emergency search and rescue, air quality inspection and other fields. However, the attitude dynamics model of the quadrotor UAV has strong nonlinearity, and the coupling relationship between states is complicated. Therefore, it is difficult to design the attitude contro...

AI Technical Summary

Problems solved by technology

However, the attitude dynamics model of the quadrotor UAV has strong nonlinearity, and the coupling relationship between the states is complex. Therefore, it is technically difficult to design the attitude controller directly using the complete attitude dynamics model.

[0003] There are usually several ways to solve this problem: one is to build a simple model first, and then add a neural network to compensate the model deviation of the system, or directly use the neural network to learn the dynamic model of the system, but the learning rate is too high Sometimes there will be an over-fitting problem and even eventually lead to system divergence; the second is to use the PID controller to directly control the attitude of the quadrotor without the model, and this method is difficult to solve the coupling problem between the channels; the third is the attitude dynamics of the aircraft Simplify the model and then design the nonlinear attitude controller

[0004] The traditional method usually uses a simplified attitude dynamics model when designing the quadrotor attitude controller, and this model is derived under the condition that the roll and pitch angles are compared, but in fact this model is different from the actual There is a large deviation in the attitude model, and the controller designed with this large deviation model is usually difficult to achieve the ideal control effect. This problem is especially obvious when the aircraft is maneuvering at a large angle.

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