Houcine Chafouk

Dynamic feedback linearization applied to asymptotic tracking: Generalization about the turbocharged diesel engine outputs choice

In this paper we apply dynamic feedback linearization to the tracking problem for a turbocharged diesel engine (TDE) equipped with exhaust gas recirculation (EGR) valve and variable geometry turbocharger (VGT). The model used here is the third-order mean-value model, a reduction of the eighth-order mean-value one, see [13], for sake of simplicity. Our goal is to track desired values of suitably chosen outputs. In fact, we first plan to control the input manifold pressure and the compressor mass flow rate instead of the air fuel ratio (AFR) and the EGR fraction. Unfortunately, the former lead to a non-minimum phase system while the latter are not accessible for measurements in a vehicle, see [7]. We thus replace the problem of tracking of desired values of the original output y (input manifold pressure and compressor mass flow rate) by that of tracking a suitably constructed modified output for which the values to be tracked are specifically chosen: namely, when the modified output ỹ approaches them, the original output converges to the desired values. Simulation results are presented.

State estimation under nonlinear state inequality constraints. A tracking application

This paper proposes a general method for dealing with state estimation under nonlinear state soft inequality constraints. This method is based on the projection approach, and then has the advantage to be compatible with any kind of state estimator. In order to be taken into account, the nonlinear constraints are linearized about the constrained state using an iterated approach. The proposed algorithm is tested on a three- dimension tracking application with nonlinear constraints on the moving body acceleration. The results are compared with those of an unconstrained Kalman filter.

Fault detection and isolation using Kalman filter bank for a wind turbine generator

In this paper, we will tackle the problem of current sensor Fault Detection and Isolation (FDI) of a doubly feed induction generator in wind turbine. First of all, the use of a Kalman filter to detect sensor fault will be illustrated. Then, the detection and the isolation of multiple and simultaneous sensor faults will be treated using a Kalman filter bank in a Generalized Observer Scheme and a Dedicated Observer Scheme respectively. The fault assessment will be performed by the Page-Hinkleys test. The processus of the FDI will be validated on a real-time test bench.

NCGPC with dynamic extension applied to a Turbocharged Diesel Engine

Abstract This paper presents a control design method applied to diesel engines equipped with a Variable Geometry Turbocharger (VGT) and an Exhaust Gas Recirculation (EGR) valve. The objective of this control is to reduce gas pollution to the fixed rate norms imposed by Euro v and Euro vi, Arnold et al. [2006] (Transport and E. E. Federation [2004] and Umweltbundesamt [2003]) without loosing the torque power of the controlled Turbocharged Diesel Engine (shortly, TDE). To achieve this, we propose to control Air Fuel Ratio (AFR) and EGR Fraction. But these variables are not accessible for measurements, Jankovic et al. [2000]. Therefore the gas pressure in the intake manifold and the compressor mass flow rate are preferred. Those outputs, however, lead to a non-minimum phase system. To avoid this, another choice of outputs is proposed which, together with a dynamic extension, yields a linearizable system with trivial zero dynamics, to which we apply Nonlinear Continuous-time Generalized Predictive Control.

Fuzzy controller of the air system of a diesel engine: Real-time simulation

In this paper a fuzzy controller is proposed to regulate the intake manifold pressure and the fresh mass airflow of diesel engines simultaneously. The instrumentation set usually embedded in a mass-produced passenger car has been considered. Unlike many multi-variable controllers, the proposed structure requires neither an internal model nor identification algorithms. In comparison to controllers embedded at present in standard engine control units (ECUs), it improves the trajectory tracking of desired outputs during simulation of EURO cycles. Because of its performance, the fuzzy controller has been implemented in an electronics control unit. Some real-time results are presented.

Fuzzy control of a turbocharged diesel engine

In this paper an innovative fuzzy controller is proposed to regulate the intake manifold pressure and the fresh mass airflow of diesel engines simultaneously. Unlike many multivariable controllers published in the literature, it requires neither an internal model nor identification algorithms. It has been designed considering the instrumentation set usually embedded in a mass-produced passenger car. Its rule-based structure has led to an algorithm, which is easy to implement. In comparison to controllers embedded at present in standard Engine Control Units (ECUs), it improves the trajectory tracking of desired outputs as noted during simulation of EURO cycles. In terms of robustness, this controller is little sensitive to the parameter disparity generally encountered in mass-produced engines.

Current sensor FDI by Generalized Observer Scheme for a generator in wind turbine

In this paper, we will tackle the problem of current sensor Fault Diagnosis and Isolation (FDI) of a doubly feed induction generator in wind turbine. First of all, the use of a Kalman filter to detect sensor fault will be illustrated. Then, the detection and the isolation of multiple sensor faults will be treated using a Kalman filter bank in a Generalized Observer Scheme. The fault assessment will be performed by the Page-Hinkleys test. The processus of the FDI will be validated on a real-time test bench.

Unconstrained NCGPC with a guaranteed closed-loop stability: Case of nonlinear SISO systems with the relative degree greater than four

This paper presents a new approach to solve a tracking problem for nonlinear minimum-phase systems with a relative degree greater than four by applying nonlinear continuous-time generalized predictive control (NCGPC). In fact, these systems present the particularity to have an unstable closed-loop behavior even if the derived NCGPC control law is applied to them. Indeed, the Routh-Hurwitz criterion of stability is not verified for the resulted linear closed-loop system. Inspired by the paper of Chen et al., see [1], our proposition consists in adding a specific (linear) term of correction to the receding horizon performance index such that the derived control law yields a companion form of controllability and observability for the linear closed-loop system. Therefore a pole-placement can be done and hence closed-loop stability achieved. Nevertheless, when the relative degree is less than or equal to four, this specific (linear) term is not necessary to be added to the criterion because closed-loop stability of the resulting linear system is achieved, by construction. Simulation results are presented to highlight the efficiency of the approach.

Soft computing approach for data validation

Terminology In this section, some useful definitions are given. Fault:An unpermitted deviation of at least one characteristic property or parameter of the system from the acceptable, usual or standard condition. Failure: A permanent interruption of a system’s ability to perform a required function under specified conditions. Error: A deviation between a measured or computed value of an output variable and its true one. Residual: A fault indicator based on a deviation between measurements and model-equation-based computations. Fault Detection: Determination of faults present in a system and the time of detection. Fault isolation: Determination of the kind, location and time of detection of a fault. Follows fault detection. Failure identification: Determination of the size and time-variant behavior of a fault. Follows fault isolation. Fault diagnosis: Determination of the kind, size, location and time of detection of a fault. Follows fault detection. Includes fault isolation and identification. Analytical redundancy: Use of more (not necessarily identical) ways to determine a variable, where one way uses a mathematical process model in analytical form.

Robust fault detection based on multimodel and interval approach. Application to a throttle valve

A multimodel approach has been set up in this paper. The purpose is to replace a nonlinear system by a linear one combined with interval analysis approach in order to take into account uncertainties in the model. Linear systems can be easily handled with interval computation. However, nonlinear systems need complex computations as set-computation based on sub-paving algorithms for example. To avoid a large amount of computation, the approach proposed herein is to decompose a nonlinear system in several linear models. Uncertain systems can take advantages of this approach called multimodel approach. In this paper a robust fault detection method based on multimodel will be presented. The detection will be made by an Interval Set-Valued Observer. The system is nonlinear and represents a throttle valve. It will be shown how the proposed method can replace advantageously an identification step by taking into account uncertainties on parameters.