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Model-free quadrotor UAV trajectory tracking controller and method based on rpd-smc and rise

A quadrotor UAV, trajectory tracking technology, applied in adaptive control, general control system, control/regulation system and other directions, can solve the high requirements of controller response speed and control domain, PD-SMC unchanged Due to the limited disturbance compensation capability and the instability of the open-loop of the quadrotor UAV system, the effects of reasonable control amount, reduced hardware configuration requirements and simple structure are achieved.

Active Publication Date: 2020-02-21
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the control of quadrotor drones remains a thorny problem
[0003] First, the quadrotor UAV system is open-loop unstable, so it has high requirements for the response speed of the controller and the control domain
[0004] Second, the quadrotor UAV is a typical underactuated nonlinear system, which leads to strong coupling between system variables
[0005] Third, quadrotor drones are highly susceptible to external disturbances such as friction, wind, etc., and model uncertainty
However, due to the difficulty in determining the upper bound of the disturbance and unknown dynamics, the parameter selection of PD-SMC is too large, resulting in unreasonable control signals output by the controller and wasting power resources.
In addition, the PD-SMC has limited ability to compensate for time-invariant disturbances

Method used

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  • Model-free quadrotor UAV trajectory tracking controller and method based on rpd-smc and rise
  • Model-free quadrotor UAV trajectory tracking controller and method based on rpd-smc and rise
  • Model-free quadrotor UAV trajectory tracking controller and method based on rpd-smc and rise

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0229] Example 1. In this example, the desired trajectory is a spatial spiral:

[0230] x d =2sin(0.2t)m,y d =2cos(0.2t)m

[0231] z d =0.2t m,ψ d = 0rad

[0232] The initial state of the quadrotor UAV is: ξ 0 =[0,2,0](m),η 0 =[0,0,0](rad). The disturbance is:

[0233]

[0234] where d S1 =0.2sin(2t+5),d S2 =0.2sin(1.5t+5),d D1 =2,d D2 = 1.

[0235] Image 6 with Figure 7 are the trajectory tracking result and position tracking error, respectively. from Image 6 with Figure 7 It can be seen that due to the lack of integral terms, the PD controller cannot effectively compensate for gravity and time-invariant disturbances, resulting in the quadrotor UAV being unable to track the desired trajectory under the PD controller. PD-SMC can overcome the shortcomings of PD controllers to a certain extent, but there are still static errors. In contrast, the RPD-SMC outer loop controller proposed by the present invention has achieved excellent control effects. Spec...

example 2

[0238] Example 2. Ben Leigh assumes that the quadrotor UAV is in a hovering state and is tracking a figure-of-eight desired trajectory in the X-Y plane. The desired trajectory is expressed as:

[0239] x d =2(1-cos(0.2t))m,y d =sin(0.4t)m,ψ d = 0rad

[0240] The initial position and attitude angle of the quadrotor UAV are ξ 0 =[0.5,0.5,5](m), η 0 =[0,0,0](rad). In addition, this example considers that the quadrotor UAV may be affected by gusts during flight, so the Gaussian function is used to simulate the gust effect to verify the robustness of the RPD-SMC+RISE controller designed in the present invention to wind disturbances . The perturbation signal looks like this:

[0241]

[0242] Depend on Figure 10 with Figure 11 It can be seen from the position tracking results and tracking error that although the initial position of the quadrotor UAV is far away from the desired trajectory, the RPD-SMC+RISE control system proposed in the present invention can control t...

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Abstract

The invention discloses a model-free quadrotor unmanned aerial vehicle trajectory tracking controller based on RPD-SMC and RISE, and a method, and a RPD-SMC controller is designed. The controller combines advantages of a proportional differential-sliding mode controller (PD-SMC) and online estimation capability of a radial basis function neural network (RBFNN) on arbitrary function. Through introducing self-adaptive RBFNN feedforward, disturbance and unknown dynamic conditions are estimated and compensated, so that selection of control parameters of the PD-SMC is more rational, to achieve objectives of reducing controlling quantity and saving electric energy. Aimed at an inner-loop control system, an error symbol integral (RISE) controller based on robustness is designed. The RISE controller can ensure rapid convergence of a posture angle and has strong robustness on disturbance. Beneficial effects are that the lyapunov theorem of stability proves stability of the inner-loop and outer-loop systems, and simulation experiment results prove that the controller has validity.

Description

technical field [0001] The invention relates to the technical field of trajectory tracking control of quadrotor UAVs, in particular to a model-free quadrotor UAV trajectory tracking controller and method based on RPD-SMC and RISE. Background technique [0002] A quadrotor drone is an unmanned aerial vehicle that can take off and land vertically. Compared with traditional helicopters, quadrotor drones have the advantages of simple structure, high maneuverability and strong load capacity. In recent years, quadrotor UAVs have been widely used in agriculture, monitoring, rescue and other fields and have attracted the attention of academia and industry. However, the control of quadrotor drones remains a thorny problem. [0003] First, the quadrotor UAV system is open-loop unstable, so it has high requirements on the response speed of the controller and the control domain. [0004] Second, the quadrotor UAV is a typical underactuated nonlinear system, which leads to strong coup...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 马昕李轾宋锐荣学文田新诚田国会李贻斌
Owner SHANDONG UNIV
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