Design of Active Fault Tolerant Control System for Air Fuel Ratio Control of Internal Combustion Engines Using Artificial Neural Networks

Muhammad Hamza Shahbaz,Arslan Ahmed Amin

doi:10.1109/access.2021.3068164

Abstract

Fault tolerant control systems can be used in the process machines such as Internal Combustion (IC) engines to achieve greater reliability and stability in the fault conditions. Thus, costly loss of production due to the unusual and unexpected shutdown of these machines can be avoided. The Air Fuel Ratio (AFR) control system is an important system in IC engines and faults in the sensors of this system will cause its shutdown creating costly production loss, therefore, fault tolerance is necessary for them. In this paper, an Active Fault Tolerant Control System (AFTCS) based on Artificial Neural Networks (ANN) has been proposed for the AFR control system of a Spark Ignition (SI) IC engine to increase its reliability. In the proposed AFTCS, a nonlinear ANN-based observer is used in the Fault Detection and Isolation (FDI) unit for the highly nonlinear sensors of the AFR system for analytical redundancy. The Lyapunov stability analysis has been utilized to design a stable system in normal and faulty conditions. The system has been implemented in MATLAB/Simulink environment to test its performance. The simulation experimental results demonstrate that the suggested system stays reliable maintaining the stability well in the fault conditions of sensors with little degradation in AFR. A comparison with the existing works demonstrates the superior performance of the proposed AFTCS for the highly nonlinear sensors of the AFR control system. The technique suggested is very effective in terms of fault robustness and is more specifically based on the nonlinear behavior of the MAP sensor compared to the existing works.

Highlights

A fault in a system is described as the variation of the parameter from the actual value
In a passive fault tolerant control system (PFTCS), no Fault Detection and Isolation (FDI) unit is inserted and all failure conditions are anticipated in the design process
The technique suggested is very effective in terms of fault robustness and is based on the nonlinear behavior of the Manifold Absolute Pressure (MAP) sensor compared to the existing works

Summary

INTRODUCTION

A fault in a system is described as the variation of the parameter from the actual value. In the references [1]–[3], detailed descriptions and applications of fault tolerant control (FTC) are provided. If the residual is determined to have surpassed the specified limit, the FDI unit declares it as a faulty condition. If the residual is greater than the threshold, an error will be declared and the faulty value will be replaced by the FDI unit with the estimated value obtained from the observer. In a passive fault tolerant control system (PFTCS), no FDI unit is inserted and all failure conditions are anticipated in the design process. The use of ANN as an active fault compensator in FTC design is limited to compensate the actuator/sensor error analytically based upon the observer-based system error principle [29]–[31]. Observer-based methods have been implemented in various applications [33]

ARTIFICIAL NEURAL NETWORK

RESEARCH METHODOLOGY

RESULTS AND DISCUSSION

COMPARISON WITH THE EXISTING WORKS

CONCLUSION