Event-triggered fixed-time adaptive fuzzy control for state-constrained stochastic nonlinear systems without feasibility conditions

Yao, Yangang; Tan, Jiyuan; Wu, Jian; Zhang, Xu

doi:10.1007/s11071-021-06633-7

Cited by 35 publications

(6 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lemma 1. [46]. For a positive definite function V(x) : R n → R , if there exists a > 0, b > 0, ℘ > 0, 0 < β 1 < 1, and…”

Section: Preliminariesmentioning

confidence: 99%

The Fixed-Time Observer-Based Adaptive Tracking Control for Aerial Flexible-Joint Robot with Input Saturation and Output Constraint

Wang

et al. 2023

Drones

View full text Add to dashboard Cite

The aerial flexible-joint robot (AFJR) manipulation system has been widely used in recent years. To handle uncertainty, the input saturation and the output constraint existing in the system, a fixed-time observer-based adaptive control scheme, is proposed (FTOAC). First, to estimate the input saturation and disturbances from the internal force between the robot and the flight platform, a fixed-time observer is designed. Second, a tangent-barrier Lyapunov function is introduced to implement the output constraint. Third, adaptive neural networks are introduced for the online identification of nonlinear unknown dynamics in the system. In addition, a fixed-time compensator is designed in this paper to eliminate the adverse effects caused by filtering errors. The stability analysis shows that all the signals of the closed-loop system are bounded, and the system satisfies the condition of fixed-time convergence. Finally, the simulation results prove the superiority of the proposed control strategy by comparing it with the previous schemes.

show abstract

“…Lemma 1. [46]. For a positive definite function V(x) : R n → R , if there exists a > 0, b > 0, ℘ > 0, 0 < β 1 < 1, and…”

Section: Preliminariesmentioning

confidence: 99%

The Fixed-Time Observer-Based Adaptive Tracking Control for Aerial Flexible-Joint Robot with Input Saturation and Output Constraint

Wang

et al. 2023

Drones

View full text Add to dashboard Cite

show abstract

“…• Different from general researches considering stateconstrained for single physical systems [25,26], the states of the robots are constrained in a range for the IRSs in convergence process in this paper. The output state of each robotic does not exceed the upper bound or low bound.…”

Section: Introduction 20mentioning

confidence: 99%

State-constrained bipartite tracking of interconnected robotic systems via hierarchical prescribed-performance control

et al. 2023

Nonlinear Dyn

View full text Add to dashboard Cite

This paper investigates the collaborative de-1 sign problem aiming to achieve state-constrained bipar-2 tite tracking of interconnected robotic systems (IRSs) 3 with prescribed performance. We propose a hierarchi-4 cal state-constrained estimator-based control frame to 5 reduce the complexity of algorithms and improve the 6 adaptation of the tracking control when the robotic-7 s are constrained to physical boundaries and external 8 environment. Without the pre-known tracking trajecto-9 ry, the estimator-based layer can estimate the tracking 10 trajectory at each time interval by the interconnected 11 topology. The position constraints are never violated 12 during the convergence process by designing of control 13 algorithms. The theoretical proof and simulation result-14 s are presented to validate the feasibility of the control 15 algorithms.

show abstract

“…In light of this, accurate identification and modeling of nonlinear systems constitute the first key step for achieving robust analysis and optimization. The T-S fuzzy models provide a powerful tool for dealing with complex nonlinear models, enhancing the robustness and interpretability of the models, thus being widely applied in industrial control systems [21][22][23]. Fuzzy models leverage fuzzy rules to capture the subtle features of nonlinear relationships, enabling accurate modeling.…”

Section: Introductionmentioning

confidence: 99%

Observer-based H∞Model Predictive Control for Nonlinear Discrete-time Systems with Bounded Disturbance

Zhang,

Liu

2024

Preprint

View full text Add to dashboard Cite

This study introduces an observer-based H∞ model predictive control strategy, designed for discrete-time nonlinear systems affected by bounded disturbances. Initially, an output-feedback control strategy is utilized to parameterize control actions over an infinite interval and to estimate the system state. This strategy is integrated into model predictive control (MPC) to achieve optimal control and state tracking within the closed-loop system. Subsequently, the Takagi-Sugeno (T-S) fuzzy logic model is employed to address the nonlinear terms of the system, and the H∞ performance index is used to mitigate the adverse effects of bounded disturbances on system output. With the assistance of Lyapunov stability theory and linear matrix inequalities (LMI) optimization method, sufficient conditions to ensure the system's asymptotic convergence are provided. To demonstrate the effectiveness of the proposed method, a numerical example and an engineering application example are presented.

show abstract

Event-triggered fixed-time adaptive fuzzy control for state-constrained stochastic nonlinear systems without feasibility conditions

Cited by 35 publications

References 46 publications

The Fixed-Time Observer-Based Adaptive Tracking Control for Aerial Flexible-Joint Robot with Input Saturation and Output Constraint

The Fixed-Time Observer-Based Adaptive Tracking Control for Aerial Flexible-Joint Robot with Input Saturation and Output Constraint

State-constrained bipartite tracking of interconnected robotic systems via hierarchical prescribed-performance control

Observer-based H∞Model Predictive Control for Nonlinear Discrete-time Systems with Bounded Disturbance

Contact Info

Product

Resources

About