Event-Triggered Fixed-time Adaptive Fuzzy Control for State-constrained Stochastic Nonlinear Systems Without Feasibility Conditions

Yao, Yangang; Tan, Jieqing; Wu, Jiasheng; Zhang, Xu

doi:10.21203/rs.3.rs-322781/v1

Cited by 6 publications

(6 citation statements)

References 8 publications

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“…• 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: 98%

State-Constrained Bipartite Tracking of Interconnected Robotic Systems Via Hierarchical Prescribed-Performance Control

et al. 2022

Preprint

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This paper investigates the collaborative design problem aiming to achieve state-constrained bipartite tracking of interconnected robotic systems (IRSs) with prescribed performance. We propose a hierarchical state-constrained estimator-based control frame to reduce the complexity of algorithms and improve the adaptation of the tracking control when the robotics are constrained to physical boundaries and external environment. Without the pre-known tracking trajectory, the estimator-based layer can estimate the tracking trajectory at each time interval by the interconnected topology. The position constraints are never violated during the convergence process by designing of control algorithms. The theoretical proof and simulation results are presented to validate the feasibility of the control algorithms.

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Section: Introduction 20mentioning

confidence: 98%

State-Constrained Bipartite Tracking of Interconnected Robotic Systems Via Hierarchical Prescribed-Performance Control

et al. 2022

Preprint

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“…Compared with the finite-time control law, the fixed-time control law has the outstanding advantage in the specific situation, and it can effectively realize the stable control at a given time. In [44], the event-triggered fixedtime adaptive fuzzy control method has been proposed for state-constrained stochastic nonlinear systems. In [45], a novel adaptive fixed-time control strategy has been proposed for a class of nonlinear bilateral teleoperation systems.…”

Section: Introductionmentioning

confidence: 99%

BLSTM-Based Adaptive Finite-Time Output-Constrained Control for a Class of AUSs with Dynamic Disturbances and Actuator Faults

Huang

Rong

Chang

et al. 2021

Mathematical Problems in Engineering

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In this paper, a BLSTM-based adaptive finite-time control structure has been constructed for a class of aerospace unmanned systems (AUSs). Firstly, a novel neural network structure possessing both the time memory characteristics and high learning speed, broad long short-term memory (BLSTM) network, has been constructed. Secondly, several nonlinear functions are utilized to transform the tracking errors into a novel state vector to guarantee the output constraints of the AUSs. Thirdly, the fractional-order control law and the corresponding adaptive laws are designed, and as a result, the adaptive finite-time control scheme has been formed. Moreover, to handle the uncertainties and the faulty elevator outputs, an inequality of the multivariable systems is utilized. Consequently, by fusing the output of the BLSTM, the transformation of the tracking errors, and the adaptive finite-time control law, a novel BLSTM-based intelligent adaptive finite-time control structure has been established for the AUSs under output constraints. The simulation results show that the proposed BLSTM-based adaptive control algorithm can achieve favorable control results for the AUSs with multiple uncertainties.

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“…It is well known that the adaptive backstepping control is a classical control methods for parametric nonlinear system [1,7]. When there are nonparametric uncertainties in nonlinear system, the unknown dynamics can be approximated by neural networks or fuzzy systems [8,9,10]. Although great achievements have been made in the tracking control of uncertain nonlinear systems, it is worth noting that all the mentioned results are based on the fact that the control coefficients of the system are known, or at least the control directions (the signs of the control coefficients) are available.…”

Section: Introductionmentioning

confidence: 99%

Adaptive tracking control for uncertain nonlinear systems subject to unknown control coefficients, state constraints, and input saturation

Wang

Lü

Yan

et al. 2021

Preprint

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This article is committed to studying the tracking control problem for a class of uncertain nonlinear system with unknown control coefficients. The system is subject to full state constraints, input saturation constraint, and external disturbances simultaneously. By introducing a hyperbolic tangent function to approximate the saturated input function, the sharp corner caused by the input saturation is avoided. In the meanwhile, an auxiliary system is constructed to compensate the resulting approximation error. By using the barrier Lyapunov function (BLF) based adaptive backsteping control, the Nussbaum-type adaptive controllers are constructed for the augmented system with unknown control direction. It not only ensures the system states are always within the constrained range, but also guarantees the tracking performance of the system, no matter whether the control direction of the system is known or not. Meanwhile, dynamic surface control (DSC) is used in the controller design, which avoids ”computation explosion” caused by the repeated derivation of virtual control law. Aiming at the nonparametric uncertainty of the system, a common adaptive law is designed by combining the unknown constant bounds of the external disturbance with the error term caused by input saturation estimation. It improves the tracking performance of the system and reduces the burden of the controller greatly. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control scheme in three scenarios.

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Event-Triggered Fixed-time Adaptive Fuzzy Control for State-constrained Stochastic Nonlinear Systems Without Feasibility Conditions

Cited by 6 publications

References 8 publications

State-Constrained Bipartite Tracking of Interconnected Robotic Systems Via Hierarchical Prescribed-Performance Control

State-Constrained Bipartite Tracking of Interconnected Robotic Systems Via Hierarchical Prescribed-Performance Control

BLSTM-Based Adaptive Finite-Time Output-Constrained Control for a Class of AUSs with Dynamic Disturbances and Actuator Faults

Adaptive tracking control for uncertain nonlinear systems subject to unknown control coefficients, state constraints, and input saturation

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