Formation control of aerial robots using virtual structure and new fuzzy-based self-tuning synchronization

2016 ◽  
Vol 39 (12) ◽  
pp. 1906-1919 ◽  
Author(s):  
Y Abbasi ◽  
S. Ali A Moosavian ◽  
Alireza B Novinzadeh

In this article, a novel guidance law derivation and new synchronization strategy are proposed for a virtual structure-based formation flight. These are designed using both aerodynamic and dynamics equations of aerial robots to facilitate implementation of the guidance and control laws. The guidance commands are derived in the form of acceleration based on a new analytical approach. These acceleration commands are converted to suitable inputs for the control system in the form of velocity, roll and pitch angles by employing an innovative strategy. In addition, a new synchronization strategy for virtual structure formation control is proposed. In this strategy, each agent utilizes the other agents’ actual position rather than their position errors. The proposed strategy is capable of shape formation flight using a passive sensor, such as vision sensors, for position detection of neighbour agents. This ability makes the proposed strategy more reliable than conventional synchronization methods. The mentioned strategy is further improved by self-tuning of the synchronization gain based on a fuzzy inference. The simulation of formation flight for a group of three fixed-wing aerial robots using six degrees of freedom models for each one reveals the merits of the proposed strategy. In fact, this approach significantly decreases the number of oscillations and corresponding amplitudes of position/orientation error for each agent. This is a crucial aspect of the mission performance for formation flight control.

2004 ◽  
Vol 126 (4) ◽  
pp. 873-879 ◽  
Author(s):  
P. Seiler ◽  
A. Pant ◽  
J. K. Hedrick

Flying in formation improves aerodynamic efficiency and, consequently, leads to an energy savings. One strategy for formation control is to follow the preceding vehicle. Many researchers have shown through simulation results and analysis of specific control laws that this strategy leads to amplification of disturbances as they propagate through the formation. This effect is known as string instability. In this paper, we show that string instability is due to a fundamental constraint on coupled feedback loops. The tradeoffs imposed by this constraint imply that predecessor following is an inherently poor strategy for formation flight control. Finally, we present two examples that demonstrate the theoretical results.


2017 ◽  
Vol 121 (1241) ◽  
pp. 877-900 ◽  
Author(s):  
Y. Xu ◽  
Z. Zhen

ABSTRACTThe Unmanned Aerial Vehicles (UAVs) become more and more popular due to various potential application fields. This paper studies the distributed leader-follower formation flight control problem of multiple UAVs with uncertain parameters for both the leader and followers. This problem has not been addressed in the literature. Most of the existing literature considers the leader-follower formation control strategy with parametric uncertainty for the followers. However, they do not take the leader parametric uncertainty into account. Meanwhile, the distributed control strategy depends on less information interactions and is more likely to avoid information conflict. The dynamic model of the UAVs is established based on the aerodynamic parameters. The establishment of the topology structure between a collection of UAVs is based on the algebraic graph theory. To handle the parametric uncertainty of the UAVs dynamics, a multivariable model reference adaptive control (MRAC) method is addressed to design the control law, which enables follower UAVs to track the leader UAV. The stability of the formation flight control system is proved by the Lyapunov theory. Simulation results show that the proposed distributed adaptive leader-following formation flight control system has stronger robustness and adaptivity than the fixed control system, as well as the existing adaptive control system.


2020 ◽  
pp. 1143-1180
Author(s):  
Haibin Duan

Formation flight for aerial robots is a rather complicated global optimum problem. Three formation flight control problems are introduced in this chapter, respectively, underlying controller parameter optimization, basic formation control and formation reconfiguration control. Two methods, Model Prediction Control (MPC) and Control Parameterization and Time Discretization (CPTD), are applied to solve the above problems. However, the selection of appropriate control parameters is still a barrier. Pigeon-Inspired Optimization (PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. Owning to its better performance of global exploration than others, the thoughts of PIO are applied to the control field to optimize the control parameters in the three aerial robot formation problems, to minimize the value of the cost function. Furthermore, comparative experimental results with a popular population-based algorithm called Particle Swarm Optimization (PSO) are given to show the feasibility, validity and superiority of PIO.


2013 ◽  
Vol 389 ◽  
pp. 623-631 ◽  
Author(s):  
Xiu Yan Wang ◽  
Ying Wang ◽  
Zong Shuai Li

For the flight control problem occurred in 3-DOF Helicopter System, reference adaptive inverse control scheme based on Fuzzy Neural Network model is designed. Firstly, fuzzy inference process of identifier and controller is achieved by using the network structure. Meanwhile, the neural network connection weights are used to express parameters of fuzzy inference. Then, back-propagation algorithm is adopted to amend the network connection weights in order to automatically identify the fuzzy model and adjust its membership functions and parameters, so that the actual system output of adaptive inverse controller control which is adjusted can track the reference model output. Finally, the simulation result of 3-DOF Helicopter System based on the scheme shows that the method is effective and feasible.


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4540
Author(s):  
Leszek Ambroziak ◽  
Maciej Ciężkowski

The following paper presents a method for the use of a virtual electric dipole potential field to control a leader-follower formation of autonomous Unmanned Aerial Vehicles (UAVs). The proposed control algorithm uses a virtual electric dipole potential field to determine the desired heading for a UAV follower. This method’s greatest advantage is the ability to rapidly change the potential field function depending on the position of the independent leader. Another advantage is that it ensures formation flight safety regardless of the positions of the initial leader or follower. Moreover, it is also possible to generate additional potential fields which guarantee obstacle and vehicle collision avoidance. The considered control system can easily be adapted to vehicles with different dynamics without the need to retune heading control channel gains and parameters. The paper closely describes and presents in detail the synthesis of the control algorithm based on vector fields obtained using scalar virtual electric dipole potential fields. The proposed control system was tested and its operation was verified through simulations. Generated potential fields as well as leader-follower flight parameters have been presented and thoroughly discussed within the paper. The obtained research results validate the effectiveness of this formation flight control method as well as prove that the described algorithm improves flight formation organization and helps ensure collision-free conditions.


2021 ◽  
Author(s):  
Jiang Jun ◽  
Boxin Zhao ◽  
Peng Zhang ◽  
Wanhui Guo ◽  
Peng Fang

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