Although everyone likes drones very much, the reality is that everyone's educational background, the demand for drones, the habits and angles of looking at problems and things are very different. Therefore, there is still a long way to go on the road of science and technology drone technology.
The most common cut-in perspective is to cut in from hardware and mathematical models.
The hardware perspective often comes from the performance and usage of hardware modules such as GPS, strong magnetometer, infrared device, monocular vision, binocular vision, IMU, etc. (in fact, many articles do not involve usage), input and output data types and so on. It is intuitive, easy to operate and easy to accept. But it is easy for everyone to build an understanding of the entire system of the drone, and fall into a specific hardware, and even forget the meaning of the hardware for the drone.
The perspective of the mathematical model often studies the model properties of the controlled object, nonlinear, non-minimum phase systems, coupling characteristics, and so on. Such a perspective is deep enough to be close to the essence of the controlled object, but the abstraction is too strong, and it is easy to cause a disconnection from the real object. Both hardware and mathematical models are important, but there are also problems that cannot be avoided. Therefore, the author chooses the "state" of the drone as the cut-in perspective. From the "state" perspective, it is easy to understand the practical meaning of hardware in the entire UAV system: it forms a feedback loop and returns the corresponding "status information" to provide the necessary feedback for the controller design.
Helicopter-type drone flapping angle structure
Four-rotor UAV flapping angle structure
The number of "states" of the drone will vary depending on the model. As you can see from the above two figures, the helicopter type drone will have two flapping angles as the description of the waving state compared to the quadrotor.
The state of the drone can be divided into two parts in "general":
Describe the six states of the "external position loop": position, x, y, z, which reflects the specific position of the drone on the three axes; speed status: u, v, w are used to describe none The man-machine itself travels in three directions along the line speed.
Describe the six states of the "internal attitude ring", attitude angle states: ∮, θ, ψ, respectively describing the roll, pitch, and yaw attitude angles of the drone; angular velocity states: p, q, r, describing the drone The rate of rotation on the three rotating axes of the fuselage.
Here, the term "outer ring" and "inner ring" are terms derived from the common controller structure in the design of the UAV controller. Intuitively, the two sets of states are in different coordinate systems, and the outer ring state is in "Darge coordinate system" (speed state information can be converted in the body coordinate system as long as the coordinate transformation):
The inner loop state is in the "body coordinate system".
As can be seen from the above figure, the error value between the “expected state†and the “true state†is obtained through the closed-loop feedback of the inner and outer loop state information, and the controllers of different structures are designed according to this error, and the required algorithms are calculated according to different algorithms. Control amount.
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