Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances

Ma, Hui; Li, Hongyi; Lu, Renquan; Huang, Tingwen

doi:10.1007/s11432-019-2680-1

Cited by 246 publications

(60 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Illustrative examples have been presented to confirm the usefulness of the proposed control approach. In our future work, the tracking control of uncertain nonlinear MASs using fuzzy sliding mode, 62 adaptive neural network 63 or event‐triggered protocol 64‐67 will be an interesting topic to be investigated deeply.…”

Section: Resultsmentioning

confidence: 99%

Sampled‐data containment control for Takagi‐Sugeno fuzzy multiagent systems with packet losses

Zhang

Dong

2020

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This article investigates the sampled-data containment control issue for nonlinear multiagent systems (MASs) with packet losses in the framework of Takagi-Sugeno fuzzy model. In the process of designing fuzzy sampled-data containment controller, a crucial factor, that is, asynchronous premise variables, is tackled via the proposed novel asynchronous premise rebuilding approach. Based on the fact that there may be packet losses in communication networks, the fuzzy sampled-data MAS is concerned as a switched version with two subsystems. Then, in the light of average dwell-time method and Lyapunov stability theory, sufficient conditions of designing fuzzy sampled-data containment controller are derived such that the states containment can be achieved for considered systems in spite of packet losses. Finally, both a numerical simulation and a Caltech multivehicle wireless test bed simulation are presented to confirm the effectiveness of the proposed control scheme.

show abstract

Section: Resultsmentioning

confidence: 99%

Sampled‐data containment control for Takagi‐Sugeno fuzzy multiagent systems with packet losses

Zhang

Dong

2020

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…Theorem 4. For nominal system (10 ) and modified cost function (11 ), the associated event-triggered approximate optimal controller is given in (49 ). Meanwhile, the critic NN weights update law is designed as (54 ) and the dynamic event-triggered condition is designed as follows:…”

Section: Stability Analysismentioning

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

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Due to the universality of non-linear system in practical application, the control problem of non-linear system has always been a research hotspot in the past few decades. And as well known, backstepping technique is one of the powerful tools for analysis and control for non-linear systems [1][2][3][4][5][6]. More details, in [7][8][9][10][11], with the help of backstepping technique, the output feedback, stabilisation control and stability issues of stochastic systems were considered.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy control for non‐strict‐feedback stochastic uncertain non‐linear systems based on event‐triggered strategy

Lian

Xia

Sun

et al. 2021

IET Control Theory & Appl

View full text Add to dashboard Cite

This paper investigates the issue of adaptive fuzzy control for a category of non-strictfeedback stochastic uncertain non-linear systems. Based on event-triggered mechanism, an adaptive fuzzy controller with a simple form is designed by combining backstepping technique with fuzzy logic system. The devised controller not only ensures the output signal tracking reference signal and all signals of the closed-loop system are bounded in probability but also reduces the communication load between controller and actuator. In addition, the feasibility of the considered event-triggered mechanism is guaranteed by eliminating Zeno behaviour. Finally, the validity of the proposed result is proved by an example. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances

Cited by 246 publications

References 47 publications

Sampled‐data containment control for Takagi‐Sugeno fuzzy multiagent systems with packet losses

Sampled‐data containment control for Takagi‐Sugeno fuzzy multiagent systems with packet losses

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

Adaptive fuzzy control for non‐strict‐feedback stochastic uncertain non‐linear systems based on event‐triggered strategy

Contact Info

Product

Resources

About