Rafika El Harabi

UIO-based fault detection and isolation for a class of neutral system

The purpose of this paper is to provide new methods for neutral system stability and diagnosis analysis. Based on Kharitonov stability, a new theorem is proposed for delay neutral system with robust control. For stabilized neutral system, an unknown input observer with new structure is then investigated to diagnosis this type of system. Tow important conditions are presented to can apply this type of observer. Analysis of the simulation results reveals that the application of proposed theorem and approach provide a comprehensive result for fault neutral system stability and diagnosis.

FDI based on causal graphical approaches for nonlinear processes

In this paper, fault detection and isolation for non linear systems using causal graphical approaches are presented. A diagnosis based on signed directed graph (qualitative model) is provided by determining initial and final responses using forward and backward propagation. Moreover, a bond graph (quantitative model) is used to generate Analytical Redundancy Relations (ARRs) through causal paths. To illustrate the effectiveness of the proposed approaches, a thermofluid system is studied and some simulations are provided.

Active fault tolerant control for uncertain system with state time-delay

An active control law design for uncertain linear systems with state time-delay is addressed in this paper, in order to guarantee dynamic performances and compensate fault effects. First, the fault tolerant control strategy is designed based on Frobenius norm by minimizing the distance between the closed-loop model of the faulty system and a reference one. Therefore, stability issue is ensured via the Modified Pseudo-Inverse Method (MPIM). Finally, simulation tests on a two stage chemical reactor train with delay recycle streams illustrate the effectiveness of the proposed control approach.

Fuzzy control of a mobile robot with two trailers

In this article, a control strategy based on fuzzy approach is proposed for mobile robots with only some states measurement feedback to ensure a stable and accurate navigation, reach a predefined target and avoid obstacle. This approach is applied to a mobile robot like a truck with two trailers attached, witch are added to raise the complexity problem. The simulation results show that the designed fuzzy controller effectively realizes the purpose of the truck/trailers system for reaching target under the restriction of obstacle avoidance.

Monitoring of Chemical Processes Using Model-Based Approach

In a chemical plant, a faulty sensor or actuator may cause process performance degradation (e.g. lower product quality) or fatal accidents (e.g. temperature run-away). For complex systems (e.g. CSTR reactors), fault detection and isolation are more complicated for the reason that some sensors cannot be placed in a desirable place. Furthermore, for some variables (concentrations, moles ...), no sensor exists. Therefore, the need for accurately monitoring process variables and interpreting their variations increases rapidly with the increase in the level of instrumentation in chemical plants. Supervision is a set of tools and methods used to operate a process in normal situation as well as in the presence of failures. Main activities concerned with supervision are real time Fault Detection and Isolation (FDI) and Fault Tolerant Control (FTC) to achieve safe operation of the system in the presence of faults. Supervision scheme is illustrated in two parts (see Fig. 1). The present paper deals with the FDI aspect using a model based approach. For reconfiguration or accommodation of the system, FTC methodology can be consulted in (Blanke M. & al., 2006).

Luenberger Observer based Sensor and Actuator Fault Detection for Chemical Reactor

Abstract Abstract In this paper, we propose the application of a principal observer based fault diagnosis approaches for chemical process. The Continuous Stirred Tank Reactor (CSTR) model with parametric uncertainties is linearized around a chosen steady state. A Lunberger observer is employed to generate conversion estimates for the CSTR using only temperature measurements. Results of numerical simulations of a no isothermal CSTR with coolant jacket dynamics are presented. An average robustness with respect to interpolation errors, disturbances and model parametric uncertainties is achieved by using the obtained Lunberger observer only for the sensor faults. But the detection of actuator fault is not achieved by this approach.

Graphical linear observers for fault detection: The DC motor case study

The present paper deals with a Luenberger observer design by using a causal graphical approach. Causal proprieties and structural analysis of a Bond Graph tool are involved to build classical linear observers. The residual sensitivity analysis improves the efficiency of the fault detection estimator. Simulation tests on a DC motor show the performance of the developed graphical linear observer in order to detect actuator faults.

Robust fault detection based on bond graph UIO observer

Motivated by recent concerns in building a totally graphical unknown input observer (UIO), a bond graph approach to design an UIO observer for linear systems with unknown inputs is re-evaluated in this paper. By using the Bond graph methodology and the geometric theory as the main tools, a simple and systematic design procedure is depicted. Compared with the classical UIO design, the built observer is a none other than the famous Luenberger observer but with higher freedom degree that ensures the decoupling of the disturbance and the estimation error. In the past, it was believed that the method is valid for control purpose. Here, a new result is obtained, namely that the method is valid also for robust fault detection purpose. On the other hand, the method is found with no previous simulation results. In this paper, a proof with simulations results on an electromechanical system will show the performance of the approach.

Fault detection and estimation based on full order unknown input Hamiltonian observers

This paper deals with a novel diagnosis framework for robust fault detection and estimation purposes by combining an ordinary Unknown Input Observer (UIO) with the port-Hamiltonian formalism. Based on energy aspect, the full order Unknown Input Hamiltonian Observer (UIHO) design scheme guarantees robust residual generation through decoupling the disturbances effects from the fault ones. The fault estimation is, then, allowed by an algebraic transformation taking into account co-energy variables. Finally, simulation tests on ladder networks illustrate the effectiveness of the theoretical development.

A graphical active fault tolerant control approach

A fault tolerant control synthesis is a key solution for great and several issues which threat system safety and may have critical and dangerous consequences especially in aeronautics, medicines and chemical industry. This is why, in this present work, an Active Fault Tolerant Control (AFTC) framework is designed using a linear adaptive observer-based fault detection and estimation tasks, into graphical aspect, and a graphical PI controller in an additive form so as to ensure a control closed-loop strategy. Motivated by benefits of the Bond Graph (BG) tool as a useful method for multidisciplinary systems and which is characterized by structural, causal and behavioral properties, the proposed approach is presented. The efficiency and the relevance of the developed AFTC are proved through simulation results on a hydraulic process with two tanks together with and without fault scenarios.