Robust adaptive fuzzy sliding mode controller for nonlinear uncertain hysteretic systems

Rebai, Aissa; Guesmi, Kamel

doi:10.1177/0142331220921024

Cited by 7 publications

(6 citation statements)

References 56 publications

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“…To reject the undesired effects of unknown nonlinear terms, on the basis of the classical adaptive backstepping method, fuzzy logic control (FLC) systems are proposed to approximate the unknown nonlinear terms from the mathematical models. Heretofore, adaptive fuzzy control has received considerable attention and some fruitful accomplishments are reported in Cui et al (2019), Lai et al (2019), Li et al (2019b), Rebai and Guesmi (2020), Su and Zhang (2019), Wang et al (2020a) and Wang et al (2021). For instance, Lai et al (2019) investigated an adaptive fuzzy control method to deal with the output tracking problem of uncertain strictly feedback nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fixed-time control for nonstrict-feedback nonlinear systems with full error constraints and actuator failures

Yue

Wang

2023

Transactions of the Institute of Measurement and Control

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This paper investigates the adaptive fixed-time tracking control problem for a class of nonstrict-feedback systems with error constraints and actuator faults. With the help of the Barrier Lyapunov Function and backstepping technical, an improved adaptive fault-tolerant controller for the nonstrict-feedback system with error constraints and actuator faults is designed. In addition, fuzzy logic systems are employed to handle uncertain nonlinear terms. It is shown that the presented control scheme can guarantee that the tracking error converges to a small neighborhood of zero, and the system errors fall within the pre-set funnel in the fixed time. Meanwhile, all the signals of the closed-loop system are bounded in the fixed time. Finally, simulation studies are given to demonstrate the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Adaptive fixed-time control for nonstrict-feedback nonlinear systems with full error constraints and actuator failures

Yue

Wang

2023

Transactions of the Institute of Measurement and Control

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“…Taking into account dead-zone input and full-state constraints, the closed-loop system states could be steered into a bounded region including the origin in a finite time. By [20], based on fuzzy logic technique, an adaptive fuzzy sliding mode control law was proposed.…”

Section: Introductionmentioning

confidence: 99%

Signum-Function-Based Multi-Input Multi-Output Adaptive Homogeneous Finite-Time Control for a Rigid-Body Attitude Tracking

Jiang

Yang

2022

Mathematical Problems in Engineering

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This study is devoted to investigating the robust adaptive finite-time attitude tracking control problem for a rigid body subject to unknown uncertainties. Considering about the nonlinear attitude dynamics for a rigid body, a homogeneous sliding variable is designed by employing the signum-function technique. For the presented homogeneous sliding variable, a real sliding manifold, on which the singularity problem is avoided, could be achieved. Subsequently, a novel signum-function-based MIMO adaptive homogeneous finite-time control (SMAHFTC) algorithm is proposed. Finite-time convergence of the tracking errors to a region around the origin is rigorously proved through the Lyapunov approach. The control gains will not be overestimated, which implies that minimal control gains will be obtained by the adaptation law. Moreover, the controls’ signals are continuous for the SMAHFTC law. Then, by means of the proposed design method, an attitude tracking controller is designed for a rigid body described by the modified Rodrigues parameters’ (MRPs) representation. A comparison simulation is carried out to show the effectiveness and superiority of the proposed method.

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“…The unknown nonlinear behavior can be approximated using fuzzy logic control. The chattering phenomena can be reduced more effectively using fuzzy logic controller as compared to PID controller [17].…”

Section: Introductionmentioning

confidence: 99%

Stabilization of liquid level in a tank system based on fuzzy logic controller

Ilyas¹,

Shah²,

Rauf

et al. 2022

IJRA

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<p>Process industry needed a fast executed automatic control system capable of handling uncertain, vague problems and nonlinear control variables. Liquid level control is one of the emerging control problems getting the interest of technical experts in the area of control. This paper is based on a fuzzy logic control strategy to maintain and stabilize the liquid level in a tank system that deals with pumping of liquid in tanks as well as regulating liquid level and pushing off the liquid into another tank. Fuzzy controller attains optimum performance by eliminating perturbation in steady state and vanishing the overshoot as compared to proportional, integral, and derivative (PID) controller. The proposed fuzzy logic controller shows minimal steady error as compared to PID controller. The defuzzification of the proposed scheme is based on the centroid method to obtain optimum results. The settling time is nearly 50 second while using fuzzy logic control as compared to 80 seconds in PID control strategy. The overshoot observed is minimal, nearly less than 1% using a fuzzy logic control scheme.</p>

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Robust adaptive fuzzy sliding mode controller for nonlinear uncertain hysteretic systems

Cited by 7 publications

References 56 publications

Adaptive fixed-time control for nonstrict-feedback nonlinear systems with full error constraints and actuator failures

Adaptive fixed-time control for nonstrict-feedback nonlinear systems with full error constraints and actuator failures

Signum-Function-Based Multi-Input Multi-Output Adaptive Homogeneous Finite-Time Control for a Rigid-Body Attitude Tracking

Stabilization of liquid level in a tank system based on fuzzy logic controller

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