基于观测器的四旋翼控制-抗扰-避障一体化

doi:10.13229/j.cnki.jdxbgxb20220592

Abstract

Abstract:

Aiming at the problem of actuator tracking error in the commonly used “planning-tracking”obstacle avoidance method for quadrotors， an obstacle avoidance position controller with obstacle constraints was proposed by adopting an integrated design scheme of control-anti-disturbance-obstacle avoidance. The Barrier Lyapunov function was used to constrain obstacle boundary. The target point becomes the balance point by introducing distance information between the aircraft and the target position， through which the problem of the unreachable target in traditional potential field methods was solved. For the problems of strong state coupling and inaccurate model building in the quadrotor control system， an observer-based model compensation control strategy is proposed and applied to the attitude control. The compensation function observer is used to estimate the model-bias and external disturbance， and then the estimated value is fed back compensated to the controller in real time to achieve the adaptive anti-disturbance control effect. Finally， the above algorithm is simulated and verified， and the results show that the observer-based model compensation control has better control effects than other control algorithms in transient performance， tracking expected response and anti-disturbance. The obstacle avoidance position controller does not need to consider the problem of tracking error. In terms of time in simulation， the integrated obstacle avoidance method is greatly shortened compared with traditional "planning-tracking" obstacle avoidance method， and static obstacle avoidance can be achieved by giving the starting and target positions.

Key words: control theory and control engineering, quadrotor unmanned aerial vehicle(UAV), control-anti-disturbance-obstacle avoidance integration, Barrier Lyapunov potential function, model compensation control （MCC）, compensation function observer （CFO）, anti-disturbance

CLC Number:

V249.12

Guo-yuan QI,Hao CHEN. Observer⁃based control⁃anti⁃disturbance⁃obstacle avoidance of quadrotor unmanned aerial vehicle[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 810-822.

Figures/Tables 18

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Table 1

Three control algorithm parameters of attitude control simulation"

控制器参数		滚转角	俯仰角	偏航角
PID	$k P$	0.40	0.40	0.44
	$k I$	0.001	0.001	0.001
	$k D$	0.07	0.07	0.1
ESO-MCC	$h$	15	15	15
	$b$	46	46	27
	$K$	［ $168$ ］	［ $168$ ］	［ $128$ ］
	$a e$	12	12	12
CFO-MCC	$h$	15	15	15
	$b$	46	46	27
	$K$	［ $168$ ］	［ $168$ ］	［ $128$ ］
	$a c$	5	5	5

Table 1

Fig.9

Fig.10

Fig.11

Fig.12

Table 2

Position channel control parameters"

参数	$z$	$x$	$y$
$a$	5	4	4
$b$	-0.714	-10	-10
$h$	15	—	—
$K$	［ $96$ ］	—	—

Table 2

Table 3

Obstacle information"

参数	障碍物1	障碍物2	障碍物3
位置	（1.5，1）	（2.5，2.5）	（4.1，3.3）
半径/m	0.4	0.5	0.5
膨胀距离/m	0.1	0.1	0.1
$k w$	0.1	0.2	0.2
$σ$	0.5	0.5	0.5

Table 3

Table 4

Position channel control other parameters"

参数		参数
$P x$	0.6	$P 3$	0.1
$P y$	0.6	$P 4$	0.1
$P 1$	0.4	$k x$	6
$P 2$	0.4	$k y$	6

Table 4

Table 5

Fig.13

References 26

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到达时间	传统方法（APF）		一体化方案
到达时间	规划	跟踪	ESO-MCC	CFO-MCC
测试时间	19.06	5.38	10.75	10.90
	18.98	5.41	11.08	11.01
	19.15	5.39	11.00	11.05
	19.11	5.32	10.75	11.00
	18.92	5.25	10.83	10.88
综合时间	24.394		10.882	10.968

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Observer⁃based control⁃anti⁃disturbance⁃obstacle avoidance of quadrotor unmanned aerial vehicle

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