Neuroadaptive Performance Guaranteed Control for Multiagent Systems With Power Integrators and Unknown Measurement Sensitivity

Liang, Hongjing; Du, Zhixu; Huang, Tingwen; Pan, Yingnan

doi:10.1109/tnnls.2022.3160532

Cited by 88 publications

(51 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the next, the COS TR of both IT2 FLSs and GT2 FLSs based on both noniterative algorithms and iterative algorithms [30,[35][36][37][38][39][40][41] will be further studies. In addition, we will investigate the applications of IT2 and GT2 fuzzy neural networks optimized with the combination of different types of intelligent algorithms [42][43][44][45][46] in forecasting, fuzzy control, and fuzzy identification and so on.…”

Section: Conclusion and Expectationsmentioning

confidence: 99%

Comparison Study of Iterative Algorithms for Center-of-Sets Type-Reduction of Takagi Sugeno Kang Type General Type-2 Fuzzy Logic Systems

Chen

2022

IEEE Access

View full text Add to dashboard Cite

Studying the block of center-of-sets (COS) type-reduction (TR) for Takagi Sugeno Kang (TSK) inference-based general type-2 fuzzy logic systems (GT2 FLSs) is meaningful for applying the systems. Blocks of fuzzy reasoning, COS type-reduction and defuzzification for TSK type GT2 FLSs are first given. According to three kinds of iterative algorithms for computing the centroids of interval type-2 fuzzy sets (IT2 FSs), the paper extends these types of algorithms for studying the COS type-reduction of TSK type GT2 FLSs. Six computer simulation experiments show the computational costs of proposed three kinds of iterative algorithms by computing the outputs of GT2 FLSs, which affords the potential guidance value designers and users of T2 FLSs.

show abstract

Section: Conclusion and Expectationsmentioning

confidence: 99%

Comparison Study of Iterative Algorithms for Center-of-Sets Type-Reduction of Takagi Sugeno Kang Type General Type-2 Fuzzy Logic Systems

Chen

2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Recently, multi-agent systems (MASs) have received widely attention by many researchers due to its various features. [1][2][3][4][5][6][7][8][9][10][11] For MASs, the consensus issue, that is leaderless consensus and leader-follower consensus, has been extensively studied. Both of the consensus problems mentioned above are used to ensure that all agents can reach a consensus based on the local information.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, multi‐agent systems (MASs) have received widely attention by many researchers due to its various features 1‐11 . For MASs, the consensus issue, that is leaderless consensus and leader‐follower consensus, has been extensively studied.…”

Section: Introductionmentioning

confidence: 99%

Observer‐based distributed fault‐tolerant containment control for stochastic nonlinear multi‐agent systems with asymmetric hysteretic quantization

Pan

Liang

2022

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

This article investigates the distributed containment control problem for high‐order stochastic nonstrict‐feedback nonlinear multi‐agent systems. To overcome the difficulty of unknown control input gain caused by the asymmetric hysteretic quantization and actuator fault, the properties of Nussbaum function are employed and an auxiliary virtual controller is designed, which does not need to estimate the bounds of the parameters of asymmetric hysteretic quantizer and efficiency factors. Moreover, the unknown terms are estimated by introducing the radial basis function neural networks. Based on the input‐driven filter, an adaptive containment control scheme is designed by using the Nussbaum function technique, the backstepping approach, and the dynamic surface control method. It is shown that the proposed control method can guarantee that all the signals are semi‐globally uniformly ultimately bounded, and the containment control performance can be achieved. Finally, some simulation results are presented to illustrate the effectiveness of the proposed approach.

show abstract

“…On the one hand, the derivative of virtual and actual control laws will tend to infinite when the tracking error approaches to zero, giving rise to singularity issues in the control design [21]. On the other hand, when the system encounters the unknown external disturbances [22][23][24][25][26], the dynamic uncertainties [27][28][29][30][31][32], the system faults [33][34][35][36], or input nonlinearities [37], it is complicated to both ensure the fixed-time stability of the system and predetermine the convergence accuracy by selecting the design parameters. As is known to us, the actuator faults not only affect handling performance for HVFs, but even cause closed-loop instability [33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Adaptive Prescribed Performance Fault-Tolerant Control for HFVs with Fixed-Time Convergence Guarantee

Dong

et al. 2022

International Journal of Aerospace Engineering

View full text Add to dashboard Cite

A new fixed-time fuzzy adaptive fault-tolerant control methodology is proposed for the longitudinal dynamics of hypersonic flight vehicles (HFVs) in the presence of actuator faults, uncertain dynamics, and external disturbances. In contrast with the conventional fixed-time control schemes that typically contain the fractional powers of errors in their designs, this work develops a low-complexity control structure in the sense of removing the dependence on the need of abovementioned fractional power terms by means of prescribed performance control (PPC) method. Different from the most existing PPC approaches where the initial conditions of tracking errors are required to be known, the newly proposed prescribed performance function (PPF) can relax such restrictions through choosing properly small initial values of PPF. Fuzzy logic systems (FLSs) are employed to handle unknown dynamics, and minimal learning parameter (MLP) technique is incorporated into the design for the purpose of alleviating computation burden. Closed-loop stability is rigorously proved via Lyapunov stability theory, and simulation results are eventually given to validate the effectiveness of the proposed control strategy.

show abstract

Neuroadaptive Performance Guaranteed Control for Multiagent Systems With Power Integrators and Unknown Measurement Sensitivity

Cited by 88 publications

References 47 publications

Comparison Study of Iterative Algorithms for Center-of-Sets Type-Reduction of Takagi Sugeno Kang Type General Type-2 Fuzzy Logic Systems

Comparison Study of Iterative Algorithms for Center-of-Sets Type-Reduction of Takagi Sugeno Kang Type General Type-2 Fuzzy Logic Systems

Observer‐based distributed fault‐tolerant containment control for stochastic nonlinear multi‐agent systems with asymmetric hysteretic quantization

Fuzzy Adaptive Prescribed Performance Fault-Tolerant Control for HFVs with Fixed-Time Convergence Guarantee

Contact Info

Product

Resources

About