Robust adaptive tracking control for nontriangular time‐delay nonlinear systems with input dead‐zone and multiple uncertainties

Xue, Lingrong; Liu, Zhen‐Guo; Wu, Yuqiang

doi:10.1002/acs.3107

Cited by 10 publications

(6 citation statements)

References 29 publications

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“…3. Compared with the results in Xue et al 25 and Cao et al, 28 the assumption of some restrictions on nonlinear functions and disturbances is removed. In the controller design, the neural network is used to approximate the nonlinear terms and external disturbances in the system, so we do not need to know whether the nonlinear terms and disturbances are prior bounded, and then manually select the control gain.…”

Section: Introductionmentioning

confidence: 95%

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Adaptive tracking control for a class of nonlinear systems with input dead‐zone and actuator failure

Lei

Chen

Wang

2022

Math Methods in App Sciences

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In this paper, the adaptive tracking problem for a class of strictly feedback nonlinear time-delay systems with output constraints, actuator failures, and input dead zones is studied. First, in the design of controller, the absolute value function and integral term are introduced into the candidate functions to deal with nonlinear factors and distributed time-varying delays in the system. In addition, an adaptive neural network controller is designed to ensure the stability of the controlled system, and the system tracking error can converge to the origin without violating the constraints. Finally, simulation results verify the feasibility of the proposed control strategy.

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Section: Introductionmentioning

confidence: 95%

“…On the other hand, the uncertain nonlinear factors in the actual system, such as dead zones [24][25][26][27] and actuator failure, [28][29][30] will lead to system instability and cause huge engineering losses. In order to ensure the normal operation of the system, some methods are proposed.…”

Section: Introductionmentioning

confidence: 99%

Adaptive tracking control for a class of nonlinear systems with input dead‐zone and actuator failure

Lei

Chen

Wang

2022

Math Methods in App Sciences

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“…On the other hand, the dead zone, as a characteristic of nonsmooth nonlinearity input, exists in many industrial processes, which may seriously effect the systems stability. The related control problems [21][22][23][24][25] have been investigated. The adaptive fuzzy control problem was addressed in Reference 22 for the uncertain non-triangular structure nonlinear systems with dead zone.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy dual‐performance fault‐tolerant control for interconnected nonlinear systems

HaoSiwen

Xuehong

PanYingnan

2021

Adaptive Control & Signal

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This article focuses on the decentralized adaptive fuzzy fixed-time fault-tolerant control issue for the error-constrained interconnected nonlinear systems with unknown actuator faults possessing dead zone. The unknown nonlinear functions can be modeled via fuzzy logic systems. By utilizing the parameter estimation method, the effect of unknown actuator faults possessing dead zone can be compensated. To guarantee the predefined dynamic performance of state tracking errors, the barrier Lyapunov functions and prescribed performance functions are introduced. Then, a dual-performance fault-tolerant control method that can guarantee fast transient performance and predefined performance of state tracking errors is proposed via using the decentralized backstepping technique. In addition, on the basis of the Lyapunov stability theory and the fixed-time criterion, it is proved that the predefined performance of full-state errors and the stability of closed-loop systems can be guaranteed. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed control scheme.

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“…On the other hand, it is worth noting that constraints are ubiquitous in engineering systems due to physical limitations, performance requirements, and safety demands 20‐23 . Violation of constraints may cause undesirable performance, degradation, hazards or system damage.…”

Section: Introductionmentioning

confidence: 99%

Adaptive cross backstepping control for a class of nonstrict feedback nonlinear systems with partial state constraints

Wang

Qilu

YuXiao

et al. 2021

Adaptive Control & Signal

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The tracking control problem for a class of partial state constrained nonlinear system is studied in this article. The system is divided into two semistrict feedback nonlinear subsystems, one is state constrained and the other is state free. By means of state transformation, the state constraint problem is transformed into the bounded problem of the transformed function. Compared with the barrier Lyapunov function (BLF) method, it not only solves the state constraint problem but also circumvents the feasibility check on virtual controllers. Based on the cross backstepping control, the constrained controller and unconstrained controller are designed simultaneously. It solves the coupling problem effectively in the design of cross processing control. On the other hand, dynamic surface control is used which effectively avoids “computation explosion” caused by backstepping control. The designed controllers can ensure the error signals converge to a small neighbourhood of zero and keep the asymmetric time‐varying constraints on system partial states are satisfied for all the time. Finally, simulation experiments are carried out on a hyperchaotic Rössler system to verify the efficacy of the control scheme.

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Robust adaptive tracking control for nontriangular time‐delay nonlinear systems with input dead‐zone and multiple uncertainties

Cited by 10 publications

References 29 publications

Adaptive tracking control for a class of nonlinear systems with input dead‐zone and actuator failure

Adaptive tracking control for a class of nonlinear systems with input dead‐zone and actuator failure

Adaptive fuzzy dual‐performance fault‐tolerant control for interconnected nonlinear systems

Adaptive cross backstepping control for a class of nonstrict feedback nonlinear systems with partial state constraints

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