Global Adaptive Leader-Following Consensus for Second-Order Nonlinear Multiagent Systems With Switching Topologies

Zou, Wencheng; Zhou, Chao; Guo, Jian; Xiang, Zhengrong

doi:10.1109/tcsii.2020.3009291

Cited by 58 publications

(30 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the output-feedback control of stochastic feedforward nonlinear systems, many important issues are still open and worth investigating, such as the generalization of the results in this paper to more general systems [32]- [38].…”

Section: Discussionmentioning

confidence: 99%

Output-Feedback Control for Stochastic Feedforward Nonlinear Systems With Markovian Switching

Wang

Yao

2022

IEEE Access

View full text Add to dashboard Cite

This paper studies the output-feedback control for stochastic feedforward nonlinear systems with Markovian switching and unknown measurement sensitivity. By developing a stochastic dualdomination design approach, a state observer and an output feedback control law are designed. By using the generalized Itô formula and Dynkin formula for Markovian switching systems, it is shown that the closedloop system has a unique solution and the solution of the closed-loop systems is almost surely asymptotically stable. Finally, a simulation example is given to illustrate the effectiveness of the control scheme.INDEX TERMS Stochastic feedforward nonlinear systems, Markovian switching, output feedback control.

show abstract

Section: Discussionmentioning

confidence: 99%

Output-Feedback Control for Stochastic Feedforward Nonlinear Systems With Markovian Switching

Wang

Yao

2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In practical applications, it is well known that the communication topology among the agents may change dramatically over time to adjust to multiple missions and complex environments [ 8 , 9 ], such as the MASs can realize obstacle avoidance and higher flight efficiency by formation transformation [ 10 , 11 ]. The design flexibility, security, and performance of convergence will be improved, which motivated the studies on the switching topologies of MASs [ 1 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Intelligent L2-L∞ Consensus of Multiagent Systems under Switching Topologies via Fuzzy Deep Q Learning

Cheng

Song

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

The problem of intelligent L2-L∞ consensus design for leader-followers multiagent systems (MASs) under switching topologies is investigated based on switched control theory and fuzzy deep Q learning. It is supposed that the communication topologies are time-varying, and the model of MASs under switching topologies is constructed based on switched systems. By employing linear transformation, the problem of consensus of MASs is converted into the issue of L2-L∞ control. The consensus protocol is composed of the dynamics-based protocol and learning-based protocol, where the robust control theory and deep Q learning are applied for the two parts to guarantee the prescribed performance and improve the transient performance. The multiple Lyapunov function (MLF) method and mode-dependent average dwell time (MDADT) method are combined to give the scheduling interval, which ensures stability and prescribed attenuation performance. The sufficient existing conditions of consensus protocol are given, and the solutions of the dynamics-based protocol are derived based on linear matrix inequalities (LMIs). Then, the online design of the learning-based protocol is formulated as a Markov decision process, where the fuzzy deep Q learning is utilized to compensate for the uncertainties and achieve optimal performance. The variation of the learning-based protocol is modeled as the external compensation on the dynamics-based protocol. Therefore, the convergence of the proposed protocol can be guaranteed by employing the nonfragile control theory. In the end, a numerical example is given to validate the effectiveness and superiority of the proposed method.

show abstract

“…Additionally, a group of UAVs has better robustness than a single vehicle when executing tasks. It is noteworthy that cooperative consensus control can be approximately divided into two categories according to the number of leaders, which are leader-following consensus and leaderless consensus [9][10][11][12]. The leader-following problem plays a vital role in consensus control for multi-UAVs, although leaderless consensus is useful in several application fields.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Leader-Following Consensus Tracking Control of Multiple UAVs Subject to Deception Attacks

Yan

2022

Processes

View full text Add to dashboard Cite

This article is concerned with the problem of leader-following consensus tracking control for multi-unmanned aerial vehicle (UAV) systems under deception attacks and actuator saturation. While guaranteeing the expected control performance, a novel adaptive event-triggered scheme (AETS) is developed to reduce the frequency of data transmission among UAVs and reduce the release of redundant data, where the adaptive threshold can be adjusted online according to the dynamic error instead of giving a default value. With the help of a new Lyapunov function, sufficient conditions and security criteria are developed to ensure that all following UAVs could reach secure consensus asymptotically with a leader UAV. Lastly, an illustrative example is presented to validate the effectiveness of the designed method.

show abstract

Global Adaptive Leader-Following Consensus for Second-Order Nonlinear Multiagent Systems With Switching Topologies

Cited by 58 publications

References 29 publications

Output-Feedback Control for Stochastic Feedforward Nonlinear Systems With Markovian Switching

Output-Feedback Control for Stochastic Feedforward Nonlinear Systems With Markovian Switching

Intelligent L2-L∞ Consensus of Multiagent Systems under Switching Topologies via Fuzzy Deep Q Learning

Adaptive Leader-Following Consensus Tracking Control of Multiple UAVs Subject to Deception Attacks

Contact Info

Product

Resources

About