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Dynamic adjustment neural network-based cooperative control for vehicle platoons with state constraints

Wang Ping, Gao Min, Li Junyu, Zhang Anguo

International Journal of Applied Mathematics and Computer Science

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2024

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Vol. 34, no. 2

211--224

EN

This paper addresses the challenge of managing state constraints in vehicle platoons, including maintaining safe distances and aligning velocities, which are key factors that contribute to performance degradation in platoon control. Traditional platoon control strategies, which rely on a constant time-headway policy, often lead to deteriorated performance and even instability, primarily during dynamic traffic conditions involving vehicle acceleration and deceleration. The underlying issue is the inadequacy of these methods to adapt to variable time-delays and to accurately modulate the spacing and speed among vehicles. To address these challenges, we propose a dynamic adjustment neural network (DANN) based cooperative control scheme. The proposed strategy employs neural networks to continuously learn and adjust to time varying conditions, thus enabling precise control of each vehicle’s state within the platoon. By integrating a DANN into the platoon control system, we ensure that both velocity and inter-vehicular spacing adapt in response to real-time traffic dynamics. The efficacy of our proposed control approach is validated using both Lyapunov stability theory and numeric simulation, which confirms substantial gains in stability and velocity tracking of the vehicle platoon.

2

Event-triggered cooperative control for high-order nonlinear multi-agent systems with finite-time consensus

Gong Shiyin, Zheng Meirong, Hu Jing, Zhang Anguo

International Journal of Applied Mathematics and Computer Science

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2023

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Vol. 33, no. 3

439--448

EN

An event-triggered adaptive control algorithm is proposed for cooperative tracking control of high-order nonlinear multiagent systems (MASs) with prescribed performance and full-state constraints. The algorithm combines dynamic surface technology and the backstepping recursive design method, with radial basis function neural networks (RBFNNs) used to approximate the unknown nonlinearity. The barrier Lyapunov function and finite-time stability theory are employed to prove that all agent states are semi-globally uniform and ultimately bounded, with the tracking error converging to a bounded neighborhood of zero in a finite time. Numerical simulations are provided to demonstrate the effectiveness of the proposed control scheme.

3

Key technologies and its application of gob-side entry retaining by roof cutting in a deep mine

Chen Shangyuan, Lv Qian, Yuan Yue

Archives of Mining Sciences

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2022

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Vol. 67, no. 1

55--77

EN

There are many problems associated with the surrounding rocks of the gob-side entry retaining by roof cutting (GERRC) as they are difficult to stabilise in deep mines. The following needs to be studied to understand the problems such as the pressure relief mechanism, evolution law of the surrounding-rock stress and the key technologies of GERRC in deep mines. Cracks are formed by advanced directional blasting to sever the path of stress transmission from the roof of the goaf to the roof of the entry and reduce the lateral cantilever length of the roof. Therefore the surrounding-rock stress and roof structure are optimised. The broken and expanded gangue formed by the collapse of the strata in the range of roof cutting fills the mining space adequately, which avoids a rapid pressure increase caused by the roof breaking impact and slows down the movement of overlying strata. The deformation of the deep surrounding rocks is transformed from “abrupt” to “slow”, and the surrounding-rock deformation of the retained entry in deep mines is significantly reduced. The average pressure and periodic pressure of the supports near the blasting line can be reduced by the blasting cracks to a certain extent, mainly due to the reduction of the length of the immediate roof cantilever and the effective load of the main roof. The combined support technologies for GERRC in deep mines were proposed, and field tests were performed. The monitoring results show that the coordinated control system can effectively control the deformation of deep rock masses, and all indexes can meet the requirements of the next working face after the retained entry is stabilised.

4

Neuro-adaptive cooperative control for high-order nonlinear multi-agent systems with uncertainties

Peng Cheng, Zhang Anguo, Li Junyu

International Journal of Applied Mathematics and Computer Science

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2021

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Vol. 31, no. 4

635--645

EN

The consensus problem for a class of high-order nonlinear multi-agent systems (MASs) with external disturbance and system uncertainty is studied. We design an online-update radial basis function (RBF) neural network based distributed adaptive control protocol, where the sliding model control method is also applied to eliminate the influence of the external disturbance and system uncertainty. System consensus is verified by using the Lyapunov stability theorem, and sufficient conditions for cooperative uniform ultimately boundedness (CUUB) are also derived. Two simulation examples demonstrate the effectiveness of the proposed method for both homogeneous and heterogeneous MASs.

5

A generalization of the graph Laplacian with application to a distributed consensus algorithm

Zhai G.

International Journal of Applied Mathematics and Computer Science

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2015

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Vol. 25, no. 2

353--360

EN

In order to describe the interconnection among agents with multi-dimensional states, we generalize the notion of a graph Laplacian by extending the adjacency weights (or weighted interconnection coefficients) from scalars to matrices. More precisely, we use positive definite matrices to denote full multi-dimensional interconnections, while using nonnegative definite matrices to denote partial multi-dimensional interconnections. We prove that the generalized graph Laplacian inherits the spectral properties of the graph Laplacian. As an application, we use the generalized graph Laplacian to establish a distributed consensus algorithm for agents described by multi-dimensional integrators.

6

Adaptive sliding mode formation control of multiple underwater robots

Das B., Subudhi B., Pati B. B.

Archives of Control Sciences

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2014

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Vol. 24, no. 4

515--543

EN

This paper proposes a new adaptive sliding mode control scheme for achieving coordinated motion control of a group of autonomous underwater vehicles with variable added mass. The control law considers the communication constraints in the acoustic medium. A common reference frame for velocity is assigned to a virtual leader dynamically. The performances of the proposed adaptive SMC were compared with that of a passivity based controller. To save the time and traveling distance for reaching the FRP by the follower AUVs, a sliding mode controller is proposed in this paper that drives the state trajectory of the AUV into a switching surface in the state space. It is observed from the obtained results that the proposed SMC provides improved performance in terms of accurately tracking the desired trajectory within less time compared to the passivity based controller. A communication consensus is designed ensuring the transfer of information among the AUVs so that they move collectively as a group. The stability of the overall closed-loop systems are analysed using Lyapunov theory and simulation results confirmed the robustness and efficiency of proposed controller.