An Adaptive Fuzzy Approach to Fault Estimation Observer Design With Actuator Fault and Digital Communication
Liheng Chen, Shasha Fu, Jianbin Qiu, Zhiguang Feng
Abstract
This article investigates the fault estimation (FE) problem for a class of nonlinear systems via an adaptive fuzzy approach. Considering the limited communication capacity of networks, the quantized measurement signals are used to construct adaptive laws instead of the real measurements in the designed fuzzy observer. By injecting the quantizer parameter into the observer inputs, the quantization effects on the convergence of estimation errors can be compensated. It is also shown that nondifferentiable actuator faults can be reconstructed by the developed FE approach. Finally, two simulation examples are provided to illustrate the validity of the presented scheme.
Topics & Concepts
Control theory (sociology)Observer (physics)ActuatorQuantization (signal processing)Nonlinear systemComputer scienceFuzzy logicFault (geology)Convergence (economics)Control engineeringAlgorithmEngineeringArtificial intelligenceControl (management)SeismologyGeologyQuantum mechanicsEconomic growthPhysicsEconomicsFault Detection and Control SystemsControl Systems and IdentificationStability and Control of Uncertain Systems