Consensus control of multi-agent systems with input and communication delay: A frequency domain perspective

Ahmed, Zahoor; Khan, Muhammad Mansoor; Saeed, Muhammad Abid; Zhang, Guoqing

doi:10.1016/j.isatra.2020.02.005

Cited by 36 publications

(39 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a result, lim t→∞ ξ i (t) = 0 can be achieved under conditions (13) and (17). In addition to that, from (11), one can prove lim t→∞xi (t) = 0 with condition (14).…”

Section: Observer Parameter Law For Stabilitymentioning

confidence: 73%

“…However, parameters in [10], [12], [14], [16] are delay-dependent, e.g., they are inverse proportional to the upper bound of delays in [10], [16] meaning delays cannot be arbitrarily large. Besides, works in [7], [8], [11] require undirected graphs.…”

Section: Observer Parameter Law For Stabilitymentioning

confidence: 99%

“…However, these LMI conditions are not scalable to arbitrarily large networks as the size of the LMI increases with the number of delays and the number of agents. Alternatively, the heterogeneous delays can be transformed into the Laplace domain and approaches in the frequency domain (e.g., generalized Nyquist criterion [6]) can be utilized to design controllers for specific dynamics of MASs, i.e., single-input-single-output (SISO) [7]- [10], first order [11], and double integrator [12]. It should be noted here that all the above agent dynamics are quite simple, which can deliver the advantage of forming the multiple transfer functions in the compact diagonal matrix format (off-diagonal elements being zero) and thus calculating each heterogeneous delay related to the corresponding single agent dynamics independently.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Consensus of General Linear Multi-Agent Systems With Heterogeneous Input and Communication Delays

Jiang

Chen

Charalambous

2021

IEEE Control Syst. Lett.

View full text Add to dashboard Cite

This paper studies the consensus tracking control for multi-agent systems (MASs) of general linear dynamics considering heterogeneous constant known input and communication delays under a directed communication graph containing a spanning tree. First, for open-loop stable MASs, a distributed predictive observer is proposed to estimate the consensus tracking error and to construct the control input that does not involve any integral term (which is time-efficient in calculation). Then, using the generalized Nyquist criterion, we derive the conditions for asymptotic convergence of the closed-loop system and show that is delay-independent. Subsequently, another observer is designed that allows the MASs to be open-loop unstable. Next, we use the generalized Nyquist criterion to compute the observer's gain matrix. Towards this end, we choose a specific structure with which the problem boils down to computing a single parameter, herein called the predictive observer parameter. Two algorithms are proposed for choosing this parameter: one for general linear systems and one for monotone systems. To the best of the authors' knowledge, this is the first work for which asymptotic convergence of consensus is proven for general linear MASs with arbitrary heterogeneous delays. Finally, the validity of our results is demonstrated via a vehicle platooning example.

show abstract

“…As a result, lim t→∞ ξ i (t) = 0 can be achieved under conditions (13) and (17). In addition to that, from (11), one can prove lim t→∞xi (t) = 0 with condition (14).…”

Section: Observer Parameter Law For Stabilitymentioning

confidence: 73%

Section: Observer Parameter Law For Stabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Consensus of General Linear Multi-Agent Systems With Heterogeneous Input and Communication Delays

Jiang

Chen

Charalambous

2021

IEEE Control Syst. Lett.

View full text Add to dashboard Cite

show abstract

“…Set k = 0. step 2 Calculate Ψ i (k) and Φ i (k) by equations (14) and (15) respectively. If the minimum condition (13) in Lemma 2 holds, go to step 3; else, exit. step 3 Calculate the residual r i (k) by equation (21).…”

Section: Outputmentioning

confidence: 99%

“…Accordingly, multi-agent systems (MASs) have received considerable attention due to their characteristics of autonomy [1], [2], distribution [3], [4] and coordination [5], [6]. Control problems of MASs have been extensively studied such as adaptive control [7], [8] and event-triggered control [9]- [11], and many results have been obtained for communication delay [12], [13]. Moreover, the fault-tolerant control problems for MASs has been recently studied by many researchers [14]- [16] because MASs are vulnerable to faults due to their structural complexity.…”

Section: Introductionmentioning

confidence: 99%

Distributed Fault Detection for Linear Time-Varying Multi-Agent Systems With Relative Output Information

Zou

Wang

2021

IEEE Access

View full text Add to dashboard Cite

This paper investigates the distributed fault detection problem for linear discrete time-varying heterogeneous multi-agent systems under relative output information. Due to the lack of absolute outputs, an augmented model is built by stacking all local relative output information. Then, the fault detection problem consisting of residual-generation and residual-evaluation is handled using the H ∞ filtering framework. The residual-generation problem is actually a minimization problem of an indefinite quadratic form, and the Krein space-Kalman filtering theory is applied, which results in a low computational burden despite the time-varying characteristic. Using the Krein space theory, a necessary and sufficient condition for the minimum is derived, and a residual-generation algorithm is developed. Further, a residual-evaluation mechanism is designed by constructing an evaluation function and detecting faults by comparing it with a threshold. Finally, two illustrative examples are given to demonstrate the effectiveness of the proposed fault detection approach.

show abstract

Distributed Observer-Based Leader-Following Consensus Control Robust to External Disturbance and Measurement Sensor Noise for LTI Multi-agent Systems

Trejo

Ponsart

Medina

et al. 2023

Recent Developments in Model-Based and Data-Driven Methods for Advanced Control and Diagnosis

View full text Add to dashboard Cite

Consensus control of multi-agent systems with input and communication delay: A frequency domain perspective

Cited by 36 publications

References 27 publications

Consensus of General Linear Multi-Agent Systems With Heterogeneous Input and Communication Delays

Consensus of General Linear Multi-Agent Systems With Heterogeneous Input and Communication Delays

Distributed Fault Detection for Linear Time-Varying Multi-Agent Systems With Relative Output Information

Distributed Observer-Based Leader-Following Consensus Control Robust to External Disturbance and Measurement Sensor Noise for LTI Multi-agent Systems

Contact Info

Product

Resources

About