Nicolas Langlois

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.

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.

Control of the air system of a diesel engine : A fuzzy multivariable approach

A new strategy based on a fuzzy multi-variable controller is proposed to regulate both the fresh airflow and the intake manifold pressure. This strategy has been designed to be implemented in a standard ECU (Electonic Control Unit) without any change of the engine instrumentation. The air system controller requires neither internal model nor certain feed-forward maps. It is intrinsically robust and very easy to tune with respect to strategies proposed in literature. The results obtained with this controller are compared to these of current embedded controllers.

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 fault-tolerant-predictive control for a class of nonlinear uncertain systems

ABSTRACT In this paper, a fault-tolerant fuzzy model-predictive control with the integral action method for a class of nonlinear uncertain systems is proposed. Nonlinear uncertain systems subject to actuators and/or sensors faults are represented by the Takagi–Sugeno (T-S) fuzzy model. The objective is to design a stable, robust and efficient fault-tolerant controller based on a T-S fuzzy observer with measurable premise variables. The proposed T-S fuzzy observer estimates state vector and faults. Based on Lyapunov theory, the trajectory tracking performances and the closed-loop system stability are analysed. The gains of the fuzzy observer and the pre-stabilized control law are obtained by solving linear matrix inequalities. Simulation results illustrate the robustness of the proposed controller with respect to uncertainties on an academic mathematical system.

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.

Sliding Mode Control for Diesel Engine Air Path Subject to Matched and Unmatched Disturbances Using Extended State Observer

The paper develops a sliding mode controller via nonlinear disturbance observer for diesel engine air path system subject to matched and unmatched disturbances. The proposed controller is based upon a novel nonlinear disturbance observer (NDO) structure which uses the concept of total disturbance estimation in order to estimate simultaneously the matched and the unmatched disturbances in the system. This estimation is then incorporated in a composite controller which alleviates the chattering problem and maintains the nominal performance of the system in the absence of disturbances. Simulations results of the proposed controller on a recently validated experimental air path diesel engine model show that the proposed methods exhibit a better performances comparing to the baseline SMC in terms of reducing chattering and nominal performances recovery.

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.

Sampled-data disturbance observer for a class of nonlinear systems

Abstract In this paper, a time varying disturbance observer subject to sampled datas measurements is proposed for a class of non-linear systems. The proposed observer combines the advantage of a high gain structure in terms of convergence speed and an output predictor which remains continuous between the sampling times. The exponential convergence of the proposed observer is proved using a Lyapunov function adapted to impulsive systems.