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Robust Adaptive Fault-Tolerant Control for a Class of Uncertain Nonlinear Time Delay Systems

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TLDR
By introducing a positive nonlinear control gain function, a bound estimation approach and an integrable auxiliary signal, the effects of the unknown time-delay functions, external disturbances, and actuator faults can be compensated completely.
Abstract
This paper is concerned with the adaptive fault-tolerant control problem for a class of Lipschitz nonlinear systems with multiple delayed-state perturbations. By introducing a positive nonlinear control gain function, a bound estimation approach and an integrable auxiliary signal, the effects of the unknown time-delay functions, external disturbances, and actuator faults can be compensated completely. It is shown that the closed-loop signals are bounded and the system state converges to zero asymptotically by the proposed control scheme. In comparing with the existing results, the time delays and actuator faults are allowed to be time varying and stuck, respectively. The obtained results are illustrated by a simulation example.

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Citations
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Journal ArticleDOI

An Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control for Robust Fault Tolerant Control of Robot Manipulators

TL;DR: A novel control methodology for tracking control of robot manipulators based on a novel adaptive backstepping nonsingular fast terminal sliding mode control (ABNFTSMC) is developed and compared with other state-of-the-art controllers.
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Event-Triggered Fault Detection Filter Design for Nonlinear Networked Systems

TL;DR: This paper investigates the problem of event-triggered fault detection (FD) filter design for nonlinear networked systems in the framework of interval type-2 fuzzy systems and proposes an augmented FD system with imperfectly matched MFs, which hampers the stability analysis and FD.
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Fuzzy Adaptive Distributed Event-Triggered Consensus Control of Uncertain Nonlinear Multiagent Systems

TL;DR: A novel distributed adaptive event-trigger condition and event-triggered controller are designed simultaneously and the main advantage with respect to event-sampling states is that the controllers were updated in an aperiodic manner at the event sampled instants, saving the computation resource and transmission load.
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Second-Order Consensus for Multiagent Systems via Intermittent Sampled Data Control

TL;DR: A novel consensus strategy is first proposed, where a periodic intermittent control strategy only with casual sampled position data is used, which not only decreases the operating time and the update rates of conditioners for every individual but also responds effectively to the case of missing velocity information.
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Adaptive Fault-Tolerant Control of Uncertain Switched Nonaffine Nonlinear Systems With Actuator Faults and Time Delays

TL;DR: By using the Lyapunov–Krasovskii stability analysis method, it is proved that the proposed adaptive switched controller can guarantee the states of the overall closed-loop systems to asymptotically converge to zero.
References
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Journal ArticleDOI

Robust control of a class of uncertain nonlinear systems

TL;DR: In this article, the robust control of a class of nonlinear systems with real-time-varying parameter uncertainty is considered and a technique is proposed for designing stabilizing controllers for both problems by converting them into scaled H∞ control problems which do not involve parameter uncertainty.
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Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints

TL;DR: Adaptive neural network control for the robotic system with full-state constraints is designed, and the adaptive NNs are adopted to handle system uncertainties and disturbances.
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Consensus of Multi-Agent Systems With General Linear and Lipschitz Nonlinear Dynamics Using Distributed Adaptive Protocols

TL;DR: This technical brief considers the distributed consensus problems for multi-agent systems with general linear and Lipschitz nonlinear dynamics and finds that the adaptive consensus protocols here can be implemented by each agent in a fully distributed fashion without using any global information.
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Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation

TL;DR: In this article, an adaptive impedance controller for a robotic manipulator with input saturation was developed by employing neural networks. But the adaptive impedance control was not considered in the tracking control design, and the input saturation is handled by designing an auxiliary system.
Journal ArticleDOI

Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems

TL;DR: Two theorems are provided to show that all the signals in the closed-loop system are bounded, the outputs are driven to follow the reference signals and all the states are ensured to remain in the predefined compact sets.
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