Iterative Learning Control Design for Multiagent Systems Based on 2D Models

Pakshin, Pavel; Emelianova, Julia; Emelianov, Mikhail

doi:10.1134/s000511791806005x

Cited by 15 publications

(6 citation statements)

References 13 publications

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“…Remark . Theorem 20 provides the sufficient condition in terms of LMIs, which belongs to the category of ILC where a consensus convergence condition is related to the learning gain matrices, the known plant knowledge and the structure of communication graph [33]. However, compared to [33], the obtained LMI condition not only provides a design method of learning gain matrices to achieve the perfect tracking of consensus, but also guarantees the monotonic convergence of the input errors and achieves the good learning transients.…”

Section: Theorem 20 Assume That Assumptions and And The Conditiomentioning

confidence: 99%

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Performance Index Based Observer‐Type Iterative Learning Control for Consensus Tracking of Uncertain Nonlinear Fractional‐Order Multiagent Systems

Wang

Zhang

2019

Complexity

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This paper is devoted to the perfect tracking problem of consensus and the monotonic convergence problem of input errors for the uncertain nonlinear fractional-order multiagent systems (FOMASs), where there exist the linear coupling relations between the fractional order, the perturbations of the system matrix, and input matrix. For the FOMASs including one leader agent and multiple follower agents, an observer-type fractional-order iterative learning consensus protocol is proposed. Based on the two-dimensional analysis for the FOMASs, a novel performance index, which can exhibit the monotonic convergence of the input errors, is constructed by using the definition of fractional integral. A Lyapunov-like method is applied to derive the sufficient conditions in terms of linear matrix inequalities, which can guarantee the perfect tracking of consensus and the monotonic convergence of input errors. Finally, the numerical simulation results including comparisons to traditional two-dimensional analysis are presented to demonstrate the effectiveness of the proposed methods.

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Section: Theorem 20 Assume That Assumptions and And The Conditiomentioning

confidence: 99%

“…The similar methods are applied to the perfect consensus problems of the nonlinear IOMASs with unknown control direction [32]. In [33], the CEF method is used to design the ILC protocol for the perfect consensus of continuous and discrete IOMASs.…”

Section: Introductionmentioning

confidence: 99%

Performance Index Based Observer‐Type Iterative Learning Control for Consensus Tracking of Uncertain Nonlinear Fractional‐Order Multiagent Systems

Wang

Zhang

2019

Complexity

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“…Linear repetitive processes under ILC are usually regarded as two-dimensional systems on the time and batch axes. Research on ILC system-design methods and convergence performance on the basis of 2D system theory has become an important direction for the development of ILC technology [10,11]. Based on the theory of 2D systems, the work in [12,13] discussed a comprehensive predictive ILC strategy to ensure the fast convergence performance of the learning process under model error and uncertain disturbance.…”

Section: Introductionmentioning

confidence: 99%

Dynamic ILC for Linear Repetitive Processes Based on Different Relative Degrees

Wang¹,

Dong

Yang³

et al. 2022

Mathematics

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The current research on iterative learning control focuses on the condition where the system relative degree is equal to 1, while the condition where the system relative degree is equal to 0 or greater than 1 is not considered. Therefore, this paper studies the monotonic convergence of the corresponding dynamic iterative learning controller systematically for discrete linear repetitive processes with different relative degrees. First, a 2D discrete Roesser model of the iterative learning control system is presented by means of 2D systems theory. Then, the monotonic convergence condition of the controlled system is analyzed according to the stability theory of linear repetitive process. Furthermore, the sufficient conditions of the controller existence are given in linear matrix inequality format under different relative degrees, which guarantees the system dynamic performance. Finally, through comparison with static controllers under different relative degrees, the simulation results show that the designed schemes are effective and feasible.

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“…To mention a few, the stability analysis problem has been studied in related works . The filtering and control problems have been investigated in other works . The fault detection problem has been considered in some other works, where a finite‐frequency fault detection method is proposed in the work of Ding et al, whereas the other studies are considered in full‐frequency domain.…”

Section: Introductionmentioning

confidence: 99%

“…[4][5][6] The filtering and control problems have been investigated in other works. [7][8][9][10] The fault detection problem has been considered in some other works, [11][12][13][14] where a finite-frequency fault detection method is proposed in the work of Ding et al, 13 whereas the other studies are considered in full-frequency domain. In the work of Zhao et al, 15 an integrated design method of fault diagnosis subjected to observer information is proposed, and the fault detection rate can be maximized.…”

Section: Introductionmentioning

confidence: 99%

Integrated fault detection and control for two‐dimensional Markovian jump systems

Ding

2019

Intl J Robust & Nonlinear

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Summary This paper is concerned with the problem of integrated fault detection and control for a class of two‐dimensional (2D) discrete‐time Markovian jump systems. The mathematical model of 2D Markovian jump systems is established upon the well‐known Roesser model, and a faults detection filter/controller is proposed to detect faults and meet some control specifications simultaneously. In this strategy, it takes into account both the fault detection objective and the control objective simultaneously through certain performance levels. The integrated design problem is then formulated as a multi‐objective optimization problem, which is nonconvex in essence. Furthermore, a two‐step algorithm is developed to solve this nonconvex problem. Sufficient conditions for existence of the desired fault detection filter/controller are established in terms of LMIs. A numerical example is used to demonstrate the effectiveness of the proposed method.

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Iterative Learning Control Design for Multiagent Systems Based on 2D Models

Cited by 15 publications

References 13 publications

Performance Index Based Observer‐Type Iterative Learning Control for Consensus Tracking of Uncertain Nonlinear Fractional‐Order Multiagent Systems

Performance Index Based Observer‐Type Iterative Learning Control for Consensus Tracking of Uncertain Nonlinear Fractional‐Order Multiagent Systems

Dynamic ILC for Linear Repetitive Processes Based on Different Relative Degrees

Integrated fault detection and control for two‐dimensional Markovian jump systems

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