Multi-Agent Cooperative Control Consensus: A Comparative Review

Gulzar, Muhammad Majid; Rizvi, Syed Tahir Hussain; Javed, Muhammad Yaqoob; Munir, Umer; Asif, Haleema

doi:10.3390/electronics7020022

Cited by 79 publications

(58 citation statements)

References 99 publications

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“…(A, B) is controllable, and all the poles of A are on the imaginary axis. For any γ > 0, from Lemma 3 we have there exist a solution P(γ) satisfies the Riccati inequality (5). In the rest of this paper, we omit γ for simplicity.…”

Section: Algorithm 2 Event-triggered Containment Control Algorithm Fomentioning

confidence: 99%

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Event-Triggered Containment Control of Multi-Agent Systems With High-Order Dynamics and Input Delay

Yang

et al. 2018

Electronics

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This paper studies the problem of distributed containment control for multi-agent systems with high-order dynamics and input delays. Two event-triggered control algorithms are proposed for multi-agent systems without and with input delay, respectively. The communication instants between two linked followers are determined by the event-triggering condition, and every follower can detect the event based on its own control input. For the followers, edge-based estimators are adopted to predict state differences to neighbors. Control inputs of the followers are calculated based on the predicted values of the state differences. To deal with the input delay, a delay comprehension approach is developed. It is proved that for arbitrarily large but bounded input delays, the followers can move into the convex hull spanned by the leaders asymptotically. Simulation results show the effectiveness of the proposed algorithms.Electronics 2018, 7, 343 2 of 22 strategy to solve this problem [24][25][26]. Compared with the traditional sampled-data-based control, where the measurement or control is triggered by time, the main feature of the event-triggered control is that the measurement or control action is triggered by an event condition. The event-triggered control strategy was applied in both leaderless and leader-following consensus problems for multi-agent systems in [27][28][29]. For more details, one can refer to [30] and references therein. More recently, the authors in [31][32][33] have proposed some event-triggered containment control algorithms for multi-agent systems with multiple leaders.Time-delay exists in most practical systems. So, it is very meaningful to investigate the stability of time-delay systems [34][35][36][37][38][39][40]. For multi-agent systems, the effect of time-delay is also an important problem to be considered. There are two sources of time-delay in multi-agent systems. One source is the communication among agents, which is called communication delays. The other source is the processing time for the information arrived at each agent, which is called input delays. The consensus problem for multi-agent system with communication/input delays has been extensively investigated in the literature (see [41] and references therein). For second-order multi-agent systems with time-varying delays, the containment control problem is considered in [42]. Recently, Miao et al. addressed the containment problem for second-order multi-agent systems with constant input delays [43]. An event-triggered containment control algorithm was proposed, together with conditions under which the followers will converge to the convex hull spanned by the leaders.In this paper, we consider the event-triggered containment control problem for multi-agent systems with high-order dynamics and input delay. Motivated by [29], model-based approach is developed to avoid continuous communications among followers, and edge-based estimators are designed to predict state differences to neighbors. New event-triggered containment control algorith...

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Section: Algorithm 2 Event-triggered Containment Control Algorithm Fomentioning

confidence: 99%

“…The consensus problem can be classified into leaderless consensus and leader-following consensus, according to the absence or presence of a leader. Recently, much progress has been made on both leaderless and leader-following consensus problems (see [1][2][3][4][5] and references therein).…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Containment Control of Multi-Agent Systems With High-Order Dynamics and Input Delay

Yang

et al. 2018

Electronics

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“…One of the main problems in coordination is consensus, i.e., agents agreement over a certain value of interest, depending on their states [137]. Consensus can be achieved, for example, by specifying rules of information exchange [138].…”

Section: Multi-agent Modelsmentioning

confidence: 99%

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

et al. 2020

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Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.Processes 2020, 8, 312 2 of 29 in a telecommunication system network, nodes (e.g., routers and switches) may suffer over time a degradation in their properties that may lead them to diminish their performance. However, just the daily variation on traffic demand also has an impact on such nodes performance. Unexpected, external intervention such as cyber-attacks or extreme weather conditions may affect the properties, even the topology of a telecommunication system.Intelligent distributed systems are capable of modelling how different parts of the network might work individually and collectively [10]. Ultimately, this is used as support for any decision-making system aiming to achieve better overall system functioning and its consequent performance. Intelligent distributed systems encompass autonomous learning units that can be associated with the nodes of a complex network. These intelligent network nodes are able to act independently and also interact with other nodes to pursue both individual (local) and general system-level targets. The necessary communication between individuals can be represented by links of the complex network connecting their nodes. It is natural to understand such nodes as intelligent agents within a MAS framework. Each agent separately obeying simple rules but working together with other agents makes it possible to approach complex engineering challenges. Intelligent distributed systems have been proposed in a broad range of engineered complex systems [11,12]. Precisely, the review proposed herein focuses only on engineered systems and manufacturing processes, given the wide spectrum of the approached topic. Out of this review fall, then, topics related to social systems analysis such as migration models [13,14] or online social media [15,16]. Similarly, natural systems are out of this review scope. This is the case of computational chemistry [17,18], biology [19,20], and metabolic networks [21,22].Automatic optimisation and control in an engineering system is associated with a near real-time data acquisition and an optimal decision-making. Th...

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“…The quadrotor model that is used in the consensus control and MPC is obtained by linearizing Equations (10) and (11). The small disturbance method is considered to linearize the EOMs, and the hovering condition of the quadrotor is chosen as the equilibrium reference.…”

Section: Linearization Of the Eomsmentioning

confidence: 99%

“…For example, the backstepping method considering the nonlinear quadrotor model [7,8], linear quadratic control considering the linear quadrotor model [2], consensus control, and MPC [9]. In the field of consensus formation control, a comparative review of the latest trends has been carried out in Reference [10]. The author of Reference [11] provides a theoretical framework for analyzing the consensus algorithms for multiagent networked systems.…”

Section: Introductionmentioning

confidence: 99%

Quadrotor Formation Strategies Based on Distributed Consensus and Model Predictive Controls

Chang

Shiau

2018

Applied Sciences

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In this study, the distributed consensus control and model predictive control (MPC)-based formation strategies for quadrotors are proposed. First, the formation-control problem is decoupled into horizontal and vertical motions. The distributed consensus control and MPC-based formation strategy are implemented in the follower’s horizontal formation control. In the horizontal motion, the leader tracks the given waypoints by simply using the MPC, and generates the desired formation trajectory for each follower based on its flight information, predicted trajectory, and the given formation pattern. On the other hand, the followers carry out the formation flight based on the proposed horizontal formation strategy and the desired formation trajectories generated by the leader. In the vertical motion, formation control is carried out using only the MPC for both the leader and the follower. Likewise, the leader tracks the desired altitude/climb rate and generates the desired formation trajectories for the followers, and the followers track the desired formation trajectories generated by the leader using the MPC. The optimization problem considered in the MPC differs for the horizontal and vertical motions. The problem is formulated as a quadratic programming (QP) problem for the horizontal motion, and as a linear quadratic tracker (LQT) for the vertical motion. Simulation of a comprehensive maneuver was carried out under a Matlab/Simulink environment to examine the performance of the proposed formation strategies.

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Multi-Agent Cooperative Control Consensus: A Comparative Review

Cited by 79 publications

References 99 publications

Event-Triggered Containment Control of Multi-Agent Systems With High-Order Dynamics and Input Delay

Event-Triggered Containment Control of Multi-Agent Systems With High-Order Dynamics and Input Delay

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

Quadrotor Formation Strategies Based on Distributed Consensus and Model Predictive Controls

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