Event-triggered adaptive prescribed performance control of uncertain nonlinear systems with unknown control directions

Zhao, Nannan; Ouyang, Xuan; Wu, Li‐Bing; Shi, Feng-Rui

doi:10.1016/j.isatra.2020.08.027

Cited by 45 publications

(41 citation statements)

References 38 publications

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“…and g i,ni (x) = g ni with g ni ̸ = 0 being a constant, whereas all the control direction functions g i,j (•), j = 1, 2, • • • , n i are allowed to be unknown in this paper. In addiction, more universalities on given system comparing with [34] and [36]: 1) just constrain |g i,j (•)| to have a lower bound; 2) the unknown nonlinear function f i,j (•) can be any smooth function, it does not require boundaries.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

“…Remark 2 As mentioned in Assumption 3, the target trajectory and its first-order derivative are bounded that mean fewer restrictions than [36] and [37]. Because the controller design strategy combines error transformation and smooth orientation functions, it is no longer needed to obtain higher derivatives of r i (t…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

“…1) Here we consider the more general uncertain MI-MO nonlinear systems with actuator failures, it is worth mentioning that [35] and [36] are special cases of this paper.…”

Section: Introductionmentioning

confidence: 99%

“…3) By the programming of the control form, neither the approximation strategies in [24,25] nor the higherorder derivatives of reference signals in [36][37][38] are used. As a result, the controller is simpler than comparable results in structure and calculation.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fault Compensation Control of MIMO Nonlinear Systems Subject to Unknown Control Directions

Dun

et al. 2021

Preprint

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This study is primarily focused on the issue of low-complexity prescribed performance fault compensation for multi-input and multi-output (MIMO) uncertain nonlinear systems with actuator failures, coupling states, and unknown control directions. First of all, proper logarithm-type error conversion functions and smooth orientation functions are linked to design the continuous control signals in the state feedback controller. Then, based on the idea of proof by contradiction, it is shown that the state errors converge to a predictable compact aggregate at the definite rate. Meanwhile, the boundedness of any closed-loop signals might be guaranteed. The simulation example results are delivered to demonstrate the effectiveness of the developed control strategy at last.

show abstract

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

“…1) Here we consider the more general uncertain MI-MO nonlinear systems with actuator failures, it is worth mentioning that [35] and [36] are special cases of this paper.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fault Compensation Control of MIMO Nonlinear Systems Subject to Unknown Control Directions

Dun

et al. 2021

Preprint

Self Cite

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“…Compared with time-triggered mechanisms, an event-triggered mechanism (ETM) can reduce the amount of data transmission more effectively, decrease the network load, and have higher flexibility. Thus, scholars have turned their attention to the study of ETM [1][2][3][4][5][6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Event-Triggered Adaptive Tracking Control for a Class of Unknown Stochastic Nonlinear Strict-Feedback Systems

et al. 2021

Symmetry

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In this paper, the dynamic event-triggered tracking control issue is studied for a class of unknown stochastic nonlinear systems with strict-feedback form. At first, neural networks (NNs) are used to approximate the unknown nonlinear functions. Then, a dynamic event-triggered controller (DETC) is designed through the adaptive backstepping method. Especially, the triggered threshold is dynamically adjusted. Compared with its corresponding static event-triggered mechanism (SETM), the dynamic event-triggered mechanism (DETM) can generate a larger execution interval and further save resources. Moreover, it is verified by two simulation examples that show that the closed-loop stochastic system signals are ultimately fourth moment semi-globally uniformly bounded (SGUUB).

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Command filter‐based adaptive neural event‐triggered control of MIMO pure‐feedback systems with full‐state time‐varying constraints

Zhu

Huang

Ding

et al. 2022

Adaptive Control & Signal

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Summary This article is concerned with the issue of adaptive event‐triggered control for a class of pure‐feedback multi‐input multi‐output (MIMO) nonlinear systems with full‐state time‐varying constraints. By using the hyperbolic tangent as nonlinear mapping technique, the uncertain constrained MIMO non‐affine system is changed into a novel unconstrained MIMO system. Dynamic surface control (DSC) strategy is used to solve the issue of “explosion of complexity.” Command filter is adopted to overcome the insufficient of the DSC method by the error compensation mechanism. Adaptive event‐triggered control scheme is developed for the transformed non‐affine system based on relative threshold mechanism. Radial basis function neural networks are utilized to approximate the unknown nonlinear functions. All the signals in the controlled system are proved to be semi‐globally uniformly ultimately bounded by adding to compensation signals into the whole Lyapunov function. Two simulation examples demonstrate the capability of the proposed control strategy.

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Event-triggered adaptive prescribed performance control of uncertain nonlinear systems with unknown control directions

Cited by 45 publications

References 38 publications

Fault Compensation Control of MIMO Nonlinear Systems Subject to Unknown Control Directions

Fault Compensation Control of MIMO Nonlinear Systems Subject to Unknown Control Directions

Dynamic Event-Triggered Adaptive Tracking Control for a Class of Unknown Stochastic Nonlinear Strict-Feedback Systems

Command filter‐based adaptive neural event‐triggered control of MIMO pure‐feedback systems with full‐state time‐varying constraints

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