Formation control of mobile robot systems incorporating primal-dual neural network and distributed predictive approach

Qin, Dongdong; Liu, Andong; Zhang, Dan; Ni, Hongjie

doi:10.1016/j.jfranklin.2020.09.025

Cited by 35 publications

(24 citation statements)

References 30 publications

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“…Then, the error signals X e eventually converge to a compact set O s defined in equation (30). Therefore, by Part 1, we have proved that the resulting closed-loop network signals are CSGUUB.…”

Section: There Exist Strictly Positive Parametersmentioning

confidence: 79%

“…), b 1 can be made arbitrarily large and b 2 can be made arbitrarily small. This certainly affects the compact set in equation (30).…”

Section: There Exist Strictly Positive Parametersmentioning

confidence: 99%

“…Here, some existing results on formation control for multiple EL systems are reviewed as follows. The formation of a group of mobile robots is considered in Qin et al 30 by utilizing the model predictive control approach. In Shojaei, 31 an adaptive neural proportional-integralderivative (PID) control framework is introduced for the leader-following formation of a class of EL-MASs subject to unmodeled dynamics, uncertain parameters, and external disturbances.…”

Section: Introductionmentioning

confidence: 99%

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Event-triggered formation control of n-link networked stochastic robotic manipulators

Azarbahram

Pariz

Sistani

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article proposes an event-triggered control framework to satisfy the tracking formation performance for a group of uncertain non-linear n-link robotic manipulators. The robotic manipulators are configured as a multi-agent system and they communicate over a directed graph (digraph). Furthermore, the non-linear robotic manipulator-multi-agent systems are subject to stochastic environmental loads. By introducing extra virtual controllers in the final step of the backstepping design, a total number of n event-triggering mechanisms are introduced independently for each link of all the robotic manipulator agents to update the control inputs in a fully distributed manner. More precisely, the actuator of each link of a particular agent is capable of being updated independent of other link actuator updates. A rigorous proof of the convergence of all the closed-loop signals in probability is then given and the Zeno phenomenon is excluded for the control event-triggered architectures. The simulation experiments finally quantify the effectiveness of proposed approach in terms of reducing the number of control updates and handling the stochastic environmental loads.

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Section: There Exist Strictly Positive Parametersmentioning

confidence: 79%

“…), b 1 can be made arbitrarily large and b 2 can be made arbitrarily small. This certainly affects the compact set in equation (30).…”

Section: There Exist Strictly Positive Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Event-triggered formation control of n-link networked stochastic robotic manipulators

Azarbahram

Pariz

Sistani

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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show abstract

“…while the desired yaw angle ψ di is independant of other states. Now introducing µ i and replacing (9) in (13), one can get…”

Section: Problem Formulationmentioning

confidence: 99%

“…The problem of formation control and tracking has been extensively studied in the literature [8,9,10,11,12]. Formation control techniques are usually categorized as virtual structure [13], behavior-based [14] and leader-follower [15]. Distributed consensus based formation control is another interesting approach in which all above mentioned categories can be incorporated [16].…”

Section: Introductionmentioning

confidence: 99%

Distributed time-varying formation tracking of multi-quadrotor systems with partial aperiodic sampled data

et al. 2022

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In this article, a distributed formation tracking controller is proposed for Multi-Agent Systems (MAS) consisting of quadrotors. It is considered that each quadrotor in the MAS only shares its translation position information with its neighbors. Moreover, position information is transmitted at nonuniform and asynchronous time instants. The control system is divided into an outer-loop for the position control and an inner-loop for the attitude control. A continuous-discrete time observer is used in the outer-loop to estimate both position and velocity of the the quadrotor and its neighbors using discrete position information it receives. Then, these estimated states are used to design the position controller in order to enable quadrotors to generate the required geometric shape. A finite-time attitude controller is designed to track the desired attitude as dictated by the position controller. Finally, a closed-

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Model following adaptive control for nodes in complex dynamical network via the state observer of links

Li,

Wang,

2024

Math Methods in App Sciences

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Geometrically, a complex dynamical network (CDN) can be regarded as the interconnected system composed of the node subsystem (NS) and the link subsystem (LS) coupled with each other. Guided by this idea, in order to achieve the goal of each node following asymptotically its own reference target in a CDN, this paper investigates the model following adaptive control (MFAC) problem of NS via the dynamics of links, which implies that the LS plays the important dynamic auxiliary role in the MFAC realization of nodes. Meanwhile, we focus on the condition that the links state information is unavailable, due to sensor practical application and measurement cost constraints. To obviate this restriction, we construct the asymptotical state observer for the LS. Next, to achieve the control goal of this paper, an appropriate Lyapunov candidate function is selected, by which the MFAC scheme for NS is synthesized based on the state observer of LS. Finally, the simulation example is performed to demonstrate the theoretical results in this paper.

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Formation control of mobile robot systems incorporating primal-dual neural network and distributed predictive approach

Cited by 35 publications

References 30 publications

Event-triggered formation control of n-link networked stochastic robotic manipulators

Event-triggered formation control of n-link networked stochastic robotic manipulators

Distributed time-varying formation tracking of multi-quadrotor systems with partial aperiodic sampled data

Model following adaptive control for nodes in complex dynamical network via the state observer of links

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