Prescribed Performance Adaptive Fuzzy Containment Control for Nonlinear Multiagent Systems Using Disturbance Observer

Wang, Wei; Liang, Hongjing; Pan, Yingnan; Li, Tieshan

doi:10.1109/tcyb.2020.2969499

Cited by 203 publications

(111 citation statements)

References 40 publications

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“…Step 3: Substituting the derived matrix variables (P, X ) into (15)- (20) and (27)- (32). If (15)- (20) and (27)-(32) satisfy the following form:…”

Section: Definementioning

confidence: 99%

“…Introduction. Due to the evolution of industrial engineering, many systems become the nonlinear versions, and the existing linear control approaches cannot directly cope with the nonlinear systems [13,14,25,32,37,39,45]. Takagi-Sugeno (T-S) fuzzy model [15,22], which can approximate the nonlinear systems by means of its precise approximation ability, has been widely applied in many significant results [5,31].…”

mentioning

confidence: 99%

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Event-based fault detection for interval type-2 fuzzy systems with measurement outliers

Li¹,

Han²,

Lu³

2021

Discrete &Amp; Continuous Dynamical Systems - S

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This paper investigates the event-based fault detection (FD) problem for a category of discrete-time interval type-2 fuzzy systems with measurement outliers. For the sake of decreasing the utilization of limited communication bandwidth, an event-based mechanism is introduced. Based on the saturation function technique, a novel event-based FD observer is first designed to reduce the influence of outliers in the dynamic systems. Then, on the basis of Lyapunov stability theory, sufficient conditions are provided to ensure that the error system satisfies the H∞ performance and the H∞ fault performance in different cases, respectively. In contrast to the existing event-based FD results, the false alarm, which is induced by measurement outliers, can be effectively avoided by the designed FD observer with saturation function. Lastly, some simulation results are given to verify the effectiveness of the method presented in this paper.

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“…Step 3: Substituting the derived matrix variables (P, X ) into (15)- (20) and (27)- (32). If (15)- (20) and (27)-(32) satisfy the following form:…”

Section: Definementioning

confidence: 99%

mentioning

confidence: 99%

Event-based fault detection for interval type-2 fuzzy systems with measurement outliers

Li¹,

Han²,

Lu³

2021

Discrete &Amp; Continuous Dynamical Systems - S

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“…Over the past decades, control problem has attracted respectable attention 1‐16 . The effect of the constraints exists in many practical control systems, such as physical stoppages and chemical reactor temperature.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Pan

Yang

et al. 2020

Adaptive Control & Signal

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Summary This article concentrates on an adaptive finite‐time fault‐tolerant fuzzy tracking control problem for nonstrict feedback nonlinear systems with input quantization and full‐state constraints. By utilizing the fuzzy logic systems and less adjustable parameters method, the unknown nonlinear functions are addressed in each step process. In addition, a dynamic surface control technique combined with fuzzy control is introduced to tackle the variable separation problem. The problem for the effect of quantization and unlimited number of actuator faults is tackled by a damping term with smooth function in the intermediate control law. Finite‐time stability is achieved by combining barrier Lyapunov functions and backstepping method. The finite‐time controller is designed such that all the responses of the systems are semiglobal practical finite‐time stable and ensured to remain in the predefined compact sets while tracking error converges to a small neighborhood of the origin in finite time. Finally, simulation examples are utilized to testify the validity of the investigated strategy.

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“…Function approximation techniques using neural networks or fuzzy logic systems have been applied to design approximation-based adaptive control systems, in an attempt to deal with unmatched nonparametric uncertainties (i.e, nonlinear uncertainties) (see [32]- [39] and references therein). In addition, distributed adaptive control approaches have been presented for uncertain multi-agent nonlinear systems in the strict-feedback form [40]- [44]. In these studies, unknown nonlinear functions derived from the recursive control design steps were estimated via radial basis function neural networks (RBFNNs) or fuzzy logic systems.…”

Section: Introductionmentioning

confidence: 99%

Approximation-Based Event-Triggered Control Against Unknown Injection Data in Full States and Actuator of Uncertain Lower-Triangular Nonlinear Systems

Yoo

2020

IEEE Access

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This paper addresses an approximation-based adaptive event-triggered control problem against unknown injection data in full state measurements and an actuator of systems with unknown strictfeedback nonlinearities. It is assumed that full state variables measured for state-feedback control are corrupted by unknown injection data that denote cyber attacks or fault signals, and all system nonlinearities are unknown. Owing to the corrupted state feedback information, error surfaces using exactly measured state variables become unknown during the recursive control design procedure for strict-feedback nonlinear systems. Thus, they cannot be used to implement the adaptive event-triggered controller. To address this problem, an approximation-based adaptive recursive event-triggered control design using the corrupted state variables is established to ensure that error surfaces using exactly measured state variables converge to an adjustable neighborhood of the origin in the Lyapunov sense. The adaptive controller and its event-triggering law using corrupted states are designed under uncertain injection data where the adaptive injection data compensators using the neural networks are constructed to deal with the unknown injection data effects. The stability of the closed-loop systems and the exclusion of Zeno behavior are analyzed. INDEX TERMS Event-triggered control, corrupted full state measurements, unknown injection data, dynamic surface design, unknown strict-feedback nonlinearities.

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Prescribed Performance Adaptive Fuzzy Containment Control for Nonlinear Multiagent Systems Using Disturbance Observer

Cited by 203 publications

References 40 publications

Event-based fault detection for interval type-2 fuzzy systems with measurement outliers

Event-based fault detection for interval type-2 fuzzy systems with measurement outliers

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Approximation-Based Event-Triggered Control Against Unknown Injection Data in Full States and Actuator of Uncertain Lower-Triangular Nonlinear Systems

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