Optimal tracking performance for SIMO systems with packet dropouts and control energy constraints

Jiang, Xiao‐Wei; Chen, Chaoyang; Yang, Qingsheng; Qu, Xiu-Jun; Yan, Huaicheng

doi:10.1049/iet-cta.2017.1164

Cited by 14 publications

(7 citation statements)

References 28 publications

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“…In the past decades, the researches on distributed cooperative control of multiagent systems have attracted increasing attentions for its superiority over the traditional centralized control, such as stronger robustness, less energy consumption, and more flexibility [1], which thus has brought out a series of related topics, including consensus [2][3][4], distributed optimization in smart grids [5], consensus tracking [6][7][8], optimal tracking [9][10][11][12][13], bipartite consensus/tracking [14,15], formation [16][17][18][19], formationcontainment [20][21][22], synchronization [23][24][25][26], and flocking [27]. As a special case of the multiagent system, Euler-Lagrange dynamics are more applicative in many practical rigid structure modeling, especially the networked robotic system (NRS), which has gained increasing popularity due to its extensive potential applications, including industrial manufacture, search missions, and rescue missions [28].…”

Section: Introductionmentioning

confidence: 99%

“…EBHC algorithm I(9) and(10) are used for (1) to address the time-varying formation tracking problem of the NHRS consisting of four robots in the case of one virtual leader. It is set that robot 1 is redundant and the remain ones are nonredundant, whose physical parameters are selected asm 1 � col(3.0, 2.0, 1.0)kg, l 1 � col(5.0, 4.0, 3.0)m, and r 1 � 0.5l 1 , and m i � col(3.8 + 0.1i, 3.3 + 0.1i)kg, l i � col(6.6 + 0.2i, 5.6 + 0.2i)m, and…”

mentioning

confidence: 99%

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Multiple Time-Varying Formation of Networked Heterogeneous Robotic Systems via Estimator-Based Hierarchical Cooperative Algorithms

Liang

Zhan

et al. 2020

Complexity

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This paper investigates both the time-varying formation and multiple time-varying formation tracking problems of networked heterogeneous robotic systems (NHRSs) with parameter uncertainties and external disturbances in the task space. Each robot inside can be either redundant or nonredundant. Several novel estimator-based hierarchical cooperative (EBHC) algorithms are designed to achieve both the tracking task and the possible preset subtasks for redundant robots. Besides, the designed estimator algorithms guarantee that each robot can obtain the accurate information of their corresponding leaders. By employing Lyapunov stability and input-to-state stability, sufficient conditions on the asymptotic stability of the error closed-loop system are derived. Finally, two simulation examples are presented to verify the effectiveness of the proposed algorithms.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Multiple Time-Varying Formation of Networked Heterogeneous Robotic Systems via Estimator-Based Hierarchical Cooperative Algorithms

Liang

Zhan

et al. 2020

Complexity

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“…Qi et al [36] give a fundamental conditions of stabilizability. In recent years, we have also obtained some optimal performance results of NCSs, such as upstream and downstream channels with constraints [37], channel energy constaint [38], some novel trade-off factors and constraint channels [39], discrete-time(DT) systems with quantization [15], AWGN fading channels [40], SIMO systems with packetdropouts [41]. In spite of the significant progress on optimal performance studies, there are still many gaps in the optimal performance of NCSs.…”

Section: Introductionmentioning

confidence: 99%

“…about ten years in regard to finite-dimensional, LTI NCSs. Some existing literatures above tracking performance limitations of NCSs concentrate upon simulated path models emphasizing specific fields of the wholesome case, such as [11], [15], [30], [35], [41], [42] etc. However, multiple communication constraints are often encountered in general practice, and the performance limitations problem may become more complex and realistic.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, interference noises of the reference signal (or call reference noises) is considered as the input signal in our control system performance model. This is also widely used method when studying control system performance in recent years, such as [11], [15], [29], [35], [41]- [43] et al In addition, we adopt the 2DOF controller, which can be recognized as a controller structure that achieves better performance [23], [26], because this kind of controller structure has more design freedom.…”

Section: Introductionmentioning

confidence: 99%

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Tracking Performance Limitations of MIMO Networked Control Systems with Multiple Communication Constraints

Chen,

Gui,

et al. 2019

Preprint

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In this paper, the tracking performance limitation of networked control systems (NCSs) is studied. The NCSs is considered as continuous-time linear multi-input multi-output (MIMO) systems with random reference noises. The controlled plants include unstable poles and non-minimum phase (NMP) zeros. The output feedback path is affected by multiple communication constraints. We focus on some basic communication constraints, including additive white noise (AWN), quantization noise, bandwidth, as well as encoder-decoder. The system performance is evaluated with the tracking error energy, and used a two-degree of freedom (2DOF) controller. The explicit representation of the tracking performance is given in this paper. The results indicate the tracking performance limitations rely to internal characteristics of the plant (unstable poles and NMP zeros), reference noises (the reference noise power distribution (RNPD) and its directions) and the characteristics of communication constraints. The characteristics of communication constraints include communication noise power distribution (CNPD), quantization noise power distribution (QNPD), and their distribution directions, transform bandwidth allocation (TBA), transform encoder-decoder allocation (TEA), and their allocation directions, and NMP zeros and MP part of bandwidth. Moreover, the tracking performance limitations are also affected by the angles between the each transform NMP zero direction and RNPD direction, and these angles between each transform unstable poles direction and the direction of communication constraint distribution/allocation. In addition, for MIMO NCSs, bandwidth (there are not identical two channels) always can affects the direction of unstable poles, and the channel allocation of bandwidth and encode-decode may be used for a feasible method for the performance allocation of each channels. Lastly, a instance is given for verifying the effectiveness of the theoretical outcomes.

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Optimal regulation performance of discrete time‐delay systems based on quantization and input energy constraints

Yang

Zhan

et al. 2023

Asian Journal of Control

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In this paper, we study the optimal regulation problem of networked control systems and propose a new performance index for a given discrete time‐delay system. The regulation performance of the controlled plant is investigated by considering the effects of various constraints on the communication channel such as quantization, bandwidth, and packet dropouts using frequency domain methods and two‐degree‐of‐freedom control techniques. The results show that the regulation performance is not only related to the location and direction of the non‐minimum phase zeros and unstable poles of a given system but also related to the internal time delay of the controlled plant. Packet dropouts, quantization, and bandwidth limitations can also negatively affect the optimal performance. In addition, the trade‐off of the input energy constraint can also make the optimal regulation performance suffer. Finally, the reliability of this innovative result is illustrated by some simulation examples.

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Optimal tracking performance for SIMO systems with packet dropouts and control energy constraints

Cited by 14 publications

References 28 publications

Multiple Time-Varying Formation of Networked Heterogeneous Robotic Systems via Estimator-Based Hierarchical Cooperative Algorithms

Multiple Time-Varying Formation of Networked Heterogeneous Robotic Systems via Estimator-Based Hierarchical Cooperative Algorithms

Tracking Performance Limitations of MIMO Networked Control Systems with Multiple Communication Constraints

Optimal regulation performance of discrete time‐delay systems based on quantization and input energy constraints

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