Consistency and Lyapunov Stability of Linear Discrete Descriptor Time Delay Systems: A Geometric Approach

Buzurović, Ivan; Debeljković, Dragutin Lj.; Kapor, Nenad; Simeunović, Goran

doi:10.1109/icca.2019.8899962

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Then, pre-and postmultiplying ( 14) by ξ T and ξ, respectively, yields V (k+1)−V (k) = e(k+1) T P e(k+1)−e(k) T P e(k) < 0, since A a ξ = 0 from (8). The rest of this proof follows directly from the Lyapunov theory; see, for instance, Koenig et al (2008), Buzurovic et al (2019).…”

Section: Observer Designmentioning

confidence: 99%

Observer design and a separation principle for linear discrete-time descriptor sysems

Llins

Coutinho

2020

Anais Do Congresso Brasileiro De Automática 2020

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This paper addresses the design of state observers for linear discrete-time descriptor systems. Assuming that the original descriptor system is completely observable, an equivalent (standard) state-space representation of the system is proposed which preserves the system observability. Then, an LMI based approach is proposed for designing a Luenberger-like observer. In addition, a separation principle is demonstrated considering the estimation error dynamics and the closed-loop representation of the original descriptor system. Then, the observer design is extended to cope with model disturbances in an H1 sense. The eectiveness of the proposed methodology is illustrated by numerical examples.

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Section: Observer Designmentioning

confidence: 99%

Observer design and a separation principle for linear discrete-time descriptor sysems

Llins

Coutinho

2020

Anais Do Congresso Brasileiro De Automática 2020

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show abstract

“…For example, [14] provided the necessary conditions for state convergence, using frequency domain techniques like the Nyquist criterion. References [15], [16] adopted a classic method, Lyapunov stability analysis, to prove the state convergence of the MAS. Reference [14] introduced the inputto-state stability (ISS) to evaluate the stability of the control strategy in nonlinear dynamic environment.…”

Section: Introductionmentioning

confidence: 99%

A High-Precision Collaborative Control Algorithm for Multi-Agent System Based on Enhanced Depth Image Fusion Positioning

et al. 2020

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The collaborative control of the multi-agent system (MAS) marks the trend of intelligent transportation system (ITS). However, the collaborative control of MAS with flexible sampling periods remains a challenge, because under-driven systems are prone to random delays, data loss and sensor failures in semi-unstructured environment. Against the background of the semi-unstructured environment in a Dutch greenhouse, this paper puts forward a universal collaborative motion control algorithm for the MAS of automated guided vehicles (AGVs), in the light of the first-order dynamics of the system. The proposed algorithm is called continuous-step-rotate-run (CSRR). Besides, the enhanced depth image fusion positioning (EDIFP) scheme was designed to mitigate the disturbances on the control algorithm, arising from flexible sampling periods and data loss. To verify its effectiveness, the CSRR control algorithm was tested on an MAS of three under-driven BigPan AGVs. The results demonstrate that our algorithm can collaboratively control the AGVs in an effective and stable manner. The simple algorithm offers a desirable solution to the collaborative control of various MASs. INDEX TERMS Multi-agent system (MAS), collaborative control, automated guided vehicle (AGV), enhanced depth image fusion positioning (EDIFP). II. MAS COOPERATIVE CONTROL UNDER NON-UNIFORM SAMPLING CONDITIONS A. ''BIGPAN'' AGV SYSTEM

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Consistency and Lyapunov Stability of Linear Discrete Descriptor Time Delay Systems: A Geometric Approach

Cited by 2 publications

References 18 publications

Observer design and a separation principle for linear discrete-time descriptor sysems

Observer design and a separation principle for linear discrete-time descriptor sysems

A High-Precision Collaborative Control Algorithm for Multi-Agent System Based on Enhanced Depth Image Fusion Positioning

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