L1 adaptive output-feedback fault-tolerant control for uncertain nonlinear systems subject to unmodeled actuator dynamics and faults

Abstract

This paper develops a L1 adaptive output-feedback fault-tolerant controller for uncertain nonlinear systems in the presence of unmodeled actuator dynamics and actuator faults. The proposed controller consists of the output predictor, adaptive laws, and the control law. The output predictor is a dynamic system expressed as a linear system with adaptive parameters which mean the matched uncertainties and the unmatched uncertainties. Piecewise-constant adaptive laws are designed to update the adaptive parameters so that the estimation error is driven to zero at each integration time step. The control law with low-pass filters is introduced to compensate for the performance degradation because of system uncertainties, unmodeled actuator dynamics and faults, and to guarantee the uniform boundedness of the input and output signals of the system. Two simulation examples verify the effectiveness of the proposed controller.

Design and Implementation of an L1 Adaptive Proportional Output Feedback Controller

“…This methodology found application in temperature control, as detailed in [18], while Ma and Cao [19] showcased its integration with model predictive control for multivariable nonlinear systems subject to constraints. Additionally, Ma and Cao [20] explored the application of L 1 adaptive output feedback control to general partial differential equation (PDE) systems, and Zhou et al [21] addressed uncertain nonlinear systems with unmodelled dynamics and actuator faults utilising a similar design strategy. The primary limitation of these approaches lies in their reliance on transfer function formulation, which makes the interpretation of uncertainties and reference models less intuitive compared to a state-space model formulation [22,23].…”

“…The primary limitation of these approaches lies in their reliance on transfer function formulation, which makes the interpretation of uncertainties and reference models less intuitive compared to a state-space model formulation [22,23]. Indeed, state variables offer a more comprehensive reflection of the internal characteristics of a system [21,24]. However, the main limitation of the approach presented in [22,24] is that it is restricted to non-minimum phase systems with a relative degree of one.…”

Wavelet-based multi-class support vector machine for stator fault diagnosis in induction motor

“…Besides, estimating the ITSC occurrence time utilizing this transform is impossible. In the work presented by Zhou et al (2022), the authors developed an adaptive failure controller to detect the actuator faults. A low pass filter was proposed to guarantee the uniform boundedness of the output and input signals of the used system.…”

ℒ1 Adaptive Output Feedback Control of Small Unmanned Aerial Vehicles

“…As a result, arbitrarily fast adaptation can be used without sacrificing system robustness. These characteristics make it suitable for fixed-wing UAVs control in the presence of faults and external disturbances [31][32][33][34][35][36][37][38].…”

“…In [46] L 1 adaptive output feedback control was applied for general Partial Differential Equation (PDE) systems. The design presented in [38] addressed uncertain nonlinear systems in the presence of unmodeled dynamics and actuator faults.…”