Disturbance observer-based backstepping formation control of multiple quadrotors with asymmetric output error constraints

2022 ◽  
Vol 415 ◽  
pp. 126693
Author(s):  
Fang Wang ◽  
Yali Gao ◽  
Chao Zhou ◽  
Qun Zong
Keyword(s):  
Disturbance Observer ◽  
Formation Control ◽  
Output Error

scholarly journals Broad-RBFNN-Based Intelligence Adaptive Antidisturbance Formation Control for a Class of Cluster Aerospace Unmanned Systems with Multiple High-Dynamic Uncertainties

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Erxin Gao ◽  
Xin Ning ◽  
Zheng Wang ◽  
Xiaokui Yue
Keyword(s):  
Disturbance Observer ◽  
Formation Control ◽  
Control Method ◽  
Second Order ◽  
Robust Adaptive Control ◽  
Formation Flight ◽  
Control Law ◽  
Unmanned Systems ◽  
High Dynamic ◽  
Dynamic Uncertainties

This paper investigates the antidisturbance formation control problem for a class of cluster aerospace unmanned systems (CAUSs) suffering from multisource high-dynamic uncertainties. Firstly, to estimate and compensate the uncertainties existing in CAUS coordinate dynamics, an adaptive antidisturbance formation control law, which is combined by a robust adaptive control law and the second order disturbance observer, has been designed. Secondly, aiming at the adverse influences caused by the nonlinear time-varying nonlinearities existing in the formation flight dynamics, the radial basis function neural network (RBFNN) is introduced. Furthermore, considering the rapidly varying characteristics of the aforementioned formation flight nonlinearities, a novel board RBFNN (B-RBFNN) has been constructed and utilized to improve the approximation and compensation performance. In virtue of the fusing of the B-RBFNN and the second-order disturbance observer-based adaptive formation control law, the rapid response rate and the higher control accuracy of the formation control system can be achieved. As a result, a novel B-RBFNN-based intelligence adaptive antidisturbance formation control algorithm has been established for CAUS trajectory coordination and formation flight. Numerical simulation results are proposed to illustrate the effectiveness and advantages of the proposed B-RBFNN-based intelligent adaptive formation control method for the CAUS.

Adaptive neural formation control of autonomous underactuated surface vessels based on disturbance observer with leader–follower strategy

2021 ◽  
pp. 014233122110224
Author(s):  
Chunqiang Wu ◽  
Meijiao Zhao ◽  
Cheng Min ◽  
Yueying Wang ◽  
Jun Luo
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Disturbance Observer ◽  
Formation Control ◽  
Time Varying ◽  
Adaptive Neural Network ◽  
Model Uncertainties ◽  
Dynamic Surface ◽  
Surface Vessels ◽  
Underactuated Surface Vessels

In this paper, a leader–follower formation control strategy is presented based on adaptive neural network and disturbance observer, which is aimed at resolving model uncertainties as well as the time-varying disturbances for autonomous underactuated surface vessels. The model uncertainties which can be expressed by unknown nonlinear functions are approximated and compensated by the adaptive neural network. The disturbance observer introduced can estimate time-varying disturbances and compensate them to the feedforward control loop, so as to make the external time-varying disturbances suppressed and the robustness of controller against the disturbances improved. The dynamic surface control technology is applied in the procedure of designing the controller through utilizing the backstepping method, which solves the computational explosion of the derivative of virtual control signals. Finally, through Lyapunov analysis, the stability of adaptive neural formation control system is proved and all the error signals uniformly converge to a very small range ultimately. The excellent performance of the presented formation control strategy is demonstrated through numerical simulations.

scholarly journals Integral sliding mode-based formation control of multiple unertain robots via nonlinear disturbane observer

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141667769 ◽  
Author(s):  
Dianwei Qian ◽  
Chengdong Li ◽  
Shiwen Tong ◽  
Lu Yu
Keyword(s):  
Sliding Mode Control ◽  
Disturbance Observer ◽  
Formation Control ◽  
Sliding Mode ◽  
Nonlinear Disturbance Observer ◽  
Integral Sliding Mode Control ◽  
Integral Sliding Mode ◽  
Mode Control ◽  
Control Scheme ◽  
Nonlinear Disturbance

This article proposes a control scheme for formation of maneuvers of a team of mobile robots. The control scheme integrates the integral sliding mode control method with the nonlinear disturbance observer technique. The leader–follower formation dynamics suffer from uncertainties originated from the individual robots. The uncertainties challenge the formation control of such robots. Assuming that the uncertainties are unknown but bounded, an nonlinear disturbance observer-based observer is utilized to approximate them. The observer outputs feed on an integral sliding mode control-based controller. The controller and observer are integrated into the control scheme to realize formation maneuvers despite uncertainties. The formation stability is analyzed by means of the Lyapunov’s theorem. In the sense of Lyapunov, not only the convergence of the approximation errors is guaranteed but also such a control scheme can asymptotically stabilize the formation system. Compared to the results by the sole integral sliding mode control, some simulations are presented to demonstrate the feasibility and performance of the control scheme.

Concise leader-follower formation control of underactuated unmanned surface vehicle with output error constraints

2021 ◽  
pp. 014233122110471
Author(s):  
Meijiao Zhao ◽  
Yan Peng ◽  
Yueying Wang ◽  
Dan Zhang ◽  
Jun Luo ◽  
...  
Keyword(s):  
Neural Network ◽  
Formation Control ◽  
Control Method ◽  
Dynamic Surface Control ◽  
Small Range ◽  
Dynamic Surface ◽  
Unmanned Surface Vehicle ◽  
Control Approach ◽  
Output Error ◽  
Ocean Environment

In this paper, a concise leader-follower formation control approach is presented for a group of underactuated unmanned surface vehicle with dynamic system uncertainties and external environment disturbances, where the output errors are required to be within constraints. To settle the output error constraints, a standard barrier Lyapunov function (BLF) is incorporated into the backstepping control method. Furthermore, the “differential explosion” problem of virtual control laws is avoided by introducing the dynamic surface control. To estimate the unknown dynamic terms, an adaptive neural network is designed and a nonlinear disturbance observer is adopted to compensate for the approximation errors of neural network and ocean environment disturbances. Under the constraint of output error, the presented controller based on standard BLF has simpler structure and better control performance than depended on tan-type BLF. The presented controller can ensure that the formation errors converge to a small range around zero, while the output error constraint requirements are met. All signals in the closed-loop system are bounded, and the numerical simulation further shows the effectiveness of the presented control scheme.

scholarly journals Formation Control for Multiple Quadrotor Aircraft via Fixed-time Consensus Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Xiaohua Zhang ◽  
Junli Gao ◽  
Wenfeng Zhang ◽  
Tao Zeng ◽  
Liping Ye
Keyword(s):  
Disturbance Observer ◽  
Formation Control ◽  
External Disturbance ◽  
Theoretical Method ◽  
Fixed Time ◽  
Consensus Algorithm ◽  
Time Control ◽  
Quadrotor Aircraft ◽  
Attitude Controller ◽  
Accurate Observation

This paper mainly studies the formation control problem of multiple quadrotor aircraft via fixed-time control theory. First, based on the bilimit homogeneous theory and the framework of multiagent theory, for multiaircraft, a fixed-time formation control strategy is proposed. Considering the external disturbance existing on the attitude loop of the aircraft, the corresponding fixed-time disturbance observer is designed with the observer technology. Then, a fixed-time attitude controller is designed based on the accurate observation and fast compensation from the disturbance observer. Finally, some simulations are performed to verify the effectiveness of the proposed theoretical method.

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