Othman Nasri

VPCA-based fault diagnosis of spacecraft reaction wheels

Fault detection and isolation methods based on the Principal Component Analysis (PCA) have been widely used for monitoring complex industrial processes with multiple variables and diagnosing process and sensor faults. This approach has been mainly developed for the analysis of single valued variables without considering any uncertainty in the systems. The main objective of this paper is then to develop a diagnosis process, of the chaser reaction wheels used during the rendezvous phase of the Mars Sample Return (MSR) mission, based on the Vertices Principal Component Analysis (VPCA) as an extension of the classical PCA for interval valued data. An industrial “high-fidelity” simulator of the MSR has provided a set of interval valued data describing the rotation rates of the spacecraft reaction wheels. The results have proven the efficiency of the proposed FDI approach in the diagnosing process.

Nonlinear fault tolerant systems with multiple actuator failures using progressive accommodation

This paper deals with the problem of multiple actuator failures occurring successively at different times. Based on the LQ problem, we propose two different strategies of fault tolerant control in order to accommodate the affected system. Both classic fault tolerant control strategy and progressive accommodation are investigated. The progressive accommodation is proved to be more efficient in maintaining a satisfactory performance even with the presence of the failures. An illustrative example is given to illustrate the proposed approaches.

Energy management of PV/wind/battery hybrid energy system based on batteries utilization optimization

This paper presents an Energy Management Supervisor (EMS) of a Hybrid Renewable Energy System (HRES) dedicated to supply a smart-home. The considered HRES include: a Photovoltaic (PV) generator, a wind turbine (WT) and a batteries bank, and can operate in grid connected or standalone mode. The developed EMS is based on a simple logic rules and have the objective to satisfy the local loads energy demand, ensure the energy flux management and the optimization of batteries utilization. Furthermore, the proposed EMS can determine the state and the operation mode of each HRES sub-systems and ensure the grid stability against frequency and voltage variations. The proposed EMS is validated by simulation results using MATLAB/Simulink environment.

Accommodation of successive actuator failures with optimal control for a class of nonlinear systems

In this paper, we propose a fault tolerant control strategy for nonlinear multi-failure range of systems. The strategy deals with the problem of fault tolerant control and progressive accommodation when successive actuator faults occur at different time delays. The authors present a comparison between the two strategies aiming to prove the efficiency of the progressive accommodation in preserving the faulty-system stability and an acceptable performance even when several successive failures occur. The proposed strategy is illustrated by an example.

Linear algebraic formalism for state estimation of labeled Petri Net

In this paper we present an algebraical approach for the state estimation of discrete event systems, partially observed and modeled by labeled Petri nets. Our estimation approach is based on the on-line observation of firing occurrences of some transitions to determine the set of all possible actual sequences and markings. This approach has been used to minimize the computation time and space for the state estimation using an off-line procedure.

SDK decentralized diagnosis with vertices principle component analysis

This paper presents a fault diagnosis system for a sophisticated automotive embedded system. The latter is a Smart Distance Keeping system (SDK) which is an advanced adaptative cruise control implemented in a truck. The proposed diagnosis process is applied in a decentralized manner. To provide local diagnosis to one of the SDK electronic control unit, the approach based on the vertices principal component analysis is selected. Without modeling the diagnosed system, this technique handles the imprecision into the sensors measurements.

Interval extended PCA-based fault diagnosis of spacecraft thrusters

This paper presents a comparison between the diagnosis results using tow new interval methods to detect and isolate thrusters faults of an autonomous spacecraft involved in the rendez-vous phase of the Mars Sample Return (MSR) mission. As an extension of the classical Principal Component Analysis (PCA) method to interval data, the first diagnosis approach we proposed is based on the Vertices Principal Component Analysis (VPCA) and the second one is based on an analytical approach. To develop a solid comparison between these two methods, a set of interval data provided by the MSR “high-fidelity” industrial simulator and representing the opening rates of the spacecraft thrusters has been considered. The results have proven the efficiency of both interval FDI approaches in the diagnosing process assuring the detection and the isolation of single type faults.

Hybrid and multi-controller architecture for autonomous system application to the navigation of a mobile robot

This paper deals with the problem of unicycle mobile robot navigation in cluttered environments. It presents in particular an approach which permits to verify the stability of the control architecture of mobile robot using the reachability analysis. To perform this analysis, we consider the robot as a hybrid dynamic system. The latter is modeled by an hybrid automata in order to verify the reachability property by using the interval analysis. The simulation results validate the proposed control architecture.