Finite-Time Consensus Tracking Neural Network FTC of Multi-Agent Systems

Dong, Guowei; Li, Hongyi; Ma, Hui; Lu, Renquan

doi:10.1109/tnnls.2020.2978898

Cited by 217 publications

(82 citation statements)

References 43 publications

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“…The fuzzy logic systems possess the similar approximation performance to NN, which implies that fuzzy logic systems can be used to solve the corresponding problems in our future research 60-63 . In addition, finite‐time control can be employed due to the better robustness 64,65 …”

Section: Resultsmentioning

confidence: 98%

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Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Yang

Xiao

Yin

et al. 2020

Intl J Robust & Nonlinear

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This article investigates the leader-follower consensus problem of a class of non-strict-feedback nonlinear multiagent systems with asymmetric time-varying state constraints (ATVSC) and input saturation, and an adaptive neural control scheme is developed. By introducing the distributed sliding-mode estimator, each follower can obtain the estimation of leader's trajectory and track it directly. Then, with the help of time-varying asymmetric barrier Lyapunov function and radial basis function neural networks, the controller is designed based on backstepping technique. Furthermore, the mean-value theorem and Nussbaum function are utilized to address the problems of input saturation and unknown control direction. Moreover, the number of adaptive laws is equal to that of the followers, which reduces the computational complexity. It is proved that the leader-follower consensus tracking control is achieved without violating the ATVSC, and all closed-loop signals are semiglobally uniformly ultimately bounded. Finally, the simulation results are provided to verify the effectiveness of the control scheme.

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Section: Resultsmentioning

confidence: 98%

“…[60][61][62][63][64] In addition, finite-time control can be employed due to the better robustness. 65,66 ACKNOWLEDGEMENT…”

Section: Resultsmentioning

confidence: 99%

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Yang

Xiao

Yin

et al. 2020

Intl J Robust & Nonlinear

Self Cite

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show abstract

“…[34][35][36] Therefore, it is necessary to consider the faults in the controller design. 37 While actuator fault is one of the most common faults, many fault-tolerant optimal control methods based on ADP have been developed. [38][39][40][41] In Reference 38, to handle the actuator gain and bias faults for an affine nonlinear system, a sliding mode fault-tolerant optimal controller was designed.…”

Section: Introductionmentioning

confidence: 99%

“…As we all know, there are various faults randomly occurring in real engineering systems, such as sensor faults and actuator faults, which can reduce the reliability and robustness of the controlled system 34–36 . Therefore, it is necessary to consider the faults in the controller design 37 . While actuator fault is one of the most common faults, many fault‐tolerant optimal control methods based on ADP have been developed 38–41 .…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered guaranteed cost fault‐tolerant optimal tracking control for uncertain nonlinear system via adaptive dynamic programming

Guo

Yao

Bai

et al. 2021

Intl J Robust & Nonlinear

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In this article, an event-triggered guaranteed cost optimal tracking control problem is investigated for a class of uncertain nonlinear system with partial loss of actuator effectiveness faults. To begin with, an augmented system consisted of error system and reference system is constructed to simplify the tracking controller design. Then, in order to consider both actuator faults and system uncertainties in optimal tracking control, an improved discounted cost function is developed. Furthermore, a single critic neural network adaptive dynamic programming algorithm is utilized to implement the event-based approximate optimal controller design. Different from static event-triggered mechanism, the dynamic event-triggered mechanism proposed in this article with an internal dynamic signal can further improve execution efficiency. A Lyapunov-based stability analysis is given to demonstrate the uniformly ultimately bounded stability of the closed-loop system. Finally, two typical nonlinear simulations are presented to verify the developed control method.

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“…Stability is a prior condition of the control system, so stability analysis and control problems of T-S fuzzy continuous/discrete systems have attracted a lot of attention [2]- [5]. Lyapunov stability theory [6]- [8] is the most effective method to solve the stability problems of nonlinear systems. So, using common Lyapunov function (CLF), stability and stabilisation problems of fuzzy systems are solved based on a series of LMIs [9].…”

Section: Introductionmentioning

confidence: 99%

Parallel and Nonparallel Distributed Compensation Controller Design for T-S Fuzzy Discrete Singular Systems With Distinct Difference Item Matrices

Qiao

2021

IEEE Access

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The issues of admissibility and controller design for a class of extended T-S fuzzy discrete singular systems (FDSSs) with distinct difference item matrices are discussed in this article. A new augmented system which is the equivalent of the original system is introduced to convert these distinct difference item matrices into the easy treatment form. On this basis, using the fuzzy Lyapunov function (FLF), relaxed sufficient condition is given to ensure the admissibility of unforced systems. This condition is described via strict linear matrix inequalities (LMIs), which facilitates to analyze the admissibility. Meanwhile, the design methods of parallel and nonparallel distributed compensation (PDC and Non-PDC) controllers are also proposed. Finally, the advantages of the developed admissibility and controller design approach are illustrated by three examples.

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Finite-Time Consensus Tracking Neural Network FTC of Multi-Agent Systems

Cited by 217 publications

References 43 publications

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Event‐triggered guaranteed cost fault‐tolerant optimal tracking control for uncertain nonlinear system via adaptive dynamic programming

Parallel and Nonparallel Distributed Compensation Controller Design for T-S Fuzzy Discrete Singular Systems With Distinct Difference Item Matrices

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