Robust adaptive formation control of quadcopters based on a leader–follower approach

Xuan-Mung, Nguyen; Hong, Sung Kyung

doi:10.1177/1729881419862733

Cited by 39 publications

(18 citation statements)

References 33 publications

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“…In this section, we briefly present the quadrotor dynamics model, as it was clearly introduced and verified in many previous studies [34,43,50,51]. Figure 1 illustrates the quadrotor configuration.…”

Section: Quadrotor Dynamics Model and Problem Formulationmentioning

confidence: 95%

Robust Backstepping Trajectory Tracking Control of a Quadrotor with Input Saturation via Extended State Observer

Xuan-Mung

Hong

2019

Applied Sciences

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Quadrotor unmanned aerial vehicles have become increasingly popular in several applications, and the improvement of their control performance has been documented in several studies. Nevertheless, the design of a high-performance tracking controller for aerial vehicles that reliably functions in the simultaneous presence of model uncertainties, external disturbances, and control input saturation still remains a challenge. In this paper, we present a robust backstepping trajectory tracking control of a quadrotor with input saturation. The controller design accounts for both parameterized uncertainties and external disturbances, whereas a new auxiliary system is proposed to cope with control input saturation. Taking into account that only the position and attitude of the quadrotor are measurable, we devise an extended state observer to supply the estimations of unmeasured states, model uncertainties, and external disturbances. We strictly prove the stability of the closed-loop system by using the Lyapunov theory and demonstrate the effectiveness of the proposed algorithm through numerical simulations.

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Section: Quadrotor Dynamics Model and Problem Formulationmentioning

confidence: 95%

Robust Backstepping Trajectory Tracking Control of a Quadrotor with Input Saturation via Extended State Observer

Xuan-Mung

Hong

2019

Applied Sciences

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“…Quadcopters, which are one of the most active classes of UAVs, have two pairs of motors to adjust their altitude and attitude. The reasons why quadcopters have been widely researched in many recent studies are that their practical models shrink in experiments for safety, and they have enough actuators to control their rigid body states including position and orientation [33][34][35][36]. In considering the formation control of multiple quadcopters, each agent can be treated as a point-mass system, and the outer loop dynamic model is described as a second-order dynamics.…”

Section: Application To Multiple Quadcopter Systemsmentioning

confidence: 99%

Dynamic Event-Triggered Time-Varying Formation Control of Second-Order Dynamic Agents: Application to Multiple Quadcopters Systems

2020

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This paper investigates the problem of the time-varying formation control of a second-order dynamic agent based on a distributed dynamic event-triggered algorithm. In this problem, each agent can exchange the information of its position and velocity with its neighbors via limited communication ability. Our approach provides a new dynamic event triggering mechanism to reduce the number of triggering times while maintaining satisfactory control performance. Further, a novel Lyapunov function is proposed to guarantee that the group of agents asymptotically tracks the desired time-varying formation trajectory. The practical applicability of the event triggering mechanism is also indicated by excluding the Zeno behavior in the proposed control algorithm. Finally, the validity and effectiveness of the proposed method are demonstrated via illustrative examples of the time-varying formation flight for six quadcopters.

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“…The goal there is to establish consensus protocols for the design of distributed controllers for a group of dynamic agents such that the network reaches an agreement of certain quantity of interest that depends on the states of all agents. Thereupon, consensus has become a comprehensive interdisciplinary subject where it addresses several research topics such as finite-time consensus for networks of dynamic agents [1], [2] networks with fixed topologies [3] networks with switching topologies [4], formation control [5], [6], and asynchronous consensus [7]. Examples of pioneering results in the field are, the Vicsek model [8], which considered a decentralised control approach and showed that alignment can be achieved through the heading of each agent, and the work by Jadbabaie [9], which provided a detailed mathematical proof of the Vicsek model and presented the jointly connected condition for networks with switching topology.…”

Section: Introductionmentioning

confidence: 99%

Decentralised Probabilistic Consensus Control for Stochastic Complex Dynamical Networks

Herzallah

2021

IEEE Control Syst. Lett.

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This paper is concerned with the consensus analysis and control problems for a class of stochastic complex dynamical networks (SCDNs) that consists of a large number of interconnected nodes. In particular, a unified probabilistic decentralised consensus control framework is established where decentralised randomised controllers are designed such that the individual subsystems in a network synchronise their states with each other to achieve consensus of the whole network. The proposed framework is quite general, where all the components within this framework including local controllers, systems' models, and communications between the subsystems of a complex system are modelled using probabilistic models. The general solution for arbitrary probabilistic models of the framework components is obtained then demonstrated on a class of linear Gaussian complex systems, thus obtaining the desired results. Furthermore, a numerical example is presented to illustrate the effectiveness and the usefulness of the theoretical development.

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Robust adaptive formation control of quadcopters based on a leader–follower approach

Cited by 39 publications

References 33 publications

Robust Backstepping Trajectory Tracking Control of a Quadrotor with Input Saturation via Extended State Observer

Robust Backstepping Trajectory Tracking Control of a Quadrotor with Input Saturation via Extended State Observer

Dynamic Event-Triggered Time-Varying Formation Control of Second-Order Dynamic Agents: Application to Multiple Quadcopters Systems

Decentralised Probabilistic Consensus Control for Stochastic Complex Dynamical Networks

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