Search

International audience; This paper proposes an Active Fault Tolerant Control (AFTC) framework for a quadcopter Unmanned Aerial Vehicle (UAV). The proposed framework is capable of achieving trajectory tracking, estimating states, as well as estimating and compensating for all four actuators multiplicative faults. The framework combines two optimization-based nonlinear estimation and control techniques; Nonlinear Moving Horizon Estimation (NMHE) and Nonlinear Model Predictive Control (NMPC). We formulate the NMHE algorithm such that it simultaneously estimates the states and the 4 actuators faults. These estimates are then provided to NMPC to achieve fault accommodation. To validate our proposed framework, we investigate two fault scenarios, where 4 actuators experience an abrupt and time-varying partial Loss Of Effectiveness (LOE) in the presence of noisy measurements. Finally, simulation results show satisfactory performance and prove that the proposed framework is numerically tractable and real-time applicable.

International audience; This article develops a unified framework to design fuzzy-model-based observers of general nonlinear systems for both discrete-time and continuous-time cases. This observer problem is known as a challenging task due to the mismatch caused by the unmeasurable premise variables. To deal with this major challenge, we propose to rewrite the nonlinear system as a specific fuzzy model with two types of local nonlinearities: measurable and unmeasurable. Then, a differential mean value theorem for vector-valued functions is applied to local unmeasurable nonlinearities. This allows to represent the estimation error dynamics in a special polytopic form involving measurable membership functions and unknown but bounded time-varying parameters. Using Lyapunov-based arguments, design conditions in terms of linear matrix inequalities are derived to guarantee the asymptotic convergence of the estimation error. Three illustrative examples are given to demonstrate the interests of the new fuzzy observer framework in reducing: 1) the design conservatism and 2) the numerical complexity of the fuzzy observer structure for real-world applications.

International audience; This paper presents an Unknown Input Observer (UIO) for a class of Lipschitz nonlinearsystems affected by disturbances/faults and having slow internal dynamics after the decoupling ofthe Unknown Input (UI). Thanks to the Asymptotic Decoupling notion, the constraint related to theinternal dynamics is bypassed. The nonlinear UIO presents time varying dynamics that allows toobtain the Asymptotic Decoupling notion. It will be shown that the proposed approach allows toenhance the convergence rate of the UIO. The convergence enhancement of the state estimation erroris demonstrated via a Lyapunov analysis and the established conditions are expressed in terms of LinearMatrix Inequalities. Finally, simulations will be given in order to illustrate the proposed approach withsome comparisons to existing techniques.

International audience; This note presents a new Unknown Input Observer (UIO) with adjustable performances for linear systems. It focuses on state estimation in the presence of zeros with slow dynamics. It is known that if the system has stable invariant zeros and satisfies the decoupling condition then a UIO exists. However, the invariant zeros constrain the pole placement and consequently the state estimation error convergence rate, especially, when the zeros dynamics is slow. In the proposed UIO, the exact decoupling condition is relaxed by the introduction of the asymptotic decoupling notion which allows to act on the invariant zeros and then enhance the convergence rate of the state estimation error. Numerical examples are provided to illustrate the performances of the UIO.

International audience; The aim of this article is the state estimation of uncertain polytopic dynamic systems. The parametric uncertainties affecting the system are time varying, unknown and bounded with known bounds. The objective is to determine the state estimates consisting in the smallest interval containing the real state value caused by the parametric uncertainties. This set will be characterized by the lower and upper bounds of the state trajectory. Given the uncertainty bounds, the set can be computed by a direct simulation of the system but a more accurate estimation is obtained with a Luenberger-type observer, fed with the system measurements. The proposed observer is designed to minimize the interval width of the estimates. The observer gains are obtained by solving an optimization problem under LMI constraints. The efficiency of the proposed approach is illustrated by numerical examples.

International audience; This paper presents a new approach for residual generator design for LPV systems affected by actuator faults and exogenous perturbations. It is illustrated that under some structural conditions, the faults can be estimated exactly while the perturbations are completely decoupled from the residual signals. However, if exact convergence is not ensured, some relaxed conditions are provided to maintain asymptotic fault estimation. Finally, the worst-case where the perturbations cannot be decoupled is presented and handled using H\_/H approach. A general design procedure is also provided which unifies the cited different cases, then applied in simulation to a quadrotor model to illustrate the effectiveness of the proposed approach.

International audience; In this paper, a Linear Parameter Varying (LPV) Unknown Input Observer (UIO) design for the attitude subsystem of a mass-varying quadcopter is proposed by using algebraic matrix manipulation. First, the design of UIO for LPV systems is discussed. Then, by applying the design process of UIO for the general LPV system, an LPV UIO is designed for the attitude of a mass-varying quadcopter. Simulation results in Matlab are conducted for illustrating the promising results of the paper.

International audience; The contribution of this work focuses on generating the best path for an UAV to distribute medicine to all the infected areas of an agriculture environment which contains non-convex obstacles, pest-free areas and pests-ridden areas. The algorithm for generating this trajectory can save the working time and the amount of medicine to be distributed to the whole agriculture infected areas. From the information on the map regarding the coordinates of the obstacles, non-infected areas, and infected areas, the infected areas are divided into several non-overlapping regions by using a clustering technique. There is a trade-off between the number of classes generated and the area of all the pests-ridden areas. After that, a polygon will be found to cover each of these infected regions. However, obstacles may occupy part of the area of these polygons that have been created previously. Each polygon that is occupied in part by obstacles can be further divided into a minimum number of obstacle-free convex polygons. Then, an optimal path length of boustrophedon trajectory will be created for each convex polygon that has been created for the UAV to follow. Finally, this paper deals with the process of creating a minimal path for the UAV to move between all the constructed convex polygons and generate the final trajectory for the UAV which ensures that all the infected agriculture areas will be covered by the medicine. The algorithm of the proposed method has been tested on MATLAB and can be used in precision agriculture.

International audience; This paper concerns the problem of attitude/altitude control of a quadrotor. The main contribution consists of developing a simple Linear Parameter Varying (LPV) model which includes the motor dynamics, weight, and moment of inertia variations. In addition, a robust LPV H∞ state-feedback controller is proposed. It allows us to perform both a reference trajectory tracking and disturbance rejection for attitude/altitude control of a mass-varying quadcopter. First, an augmented state which includes the integration of the trajectory errors for improving tracking control is computed. Next, to penalize the control inputs of the attitude/altitude system, weight functions are also added to the previous augmented system. Then, an H∞ state-feedback controller is designed by solving a set of Linear Matrix Inequalities (LMI) obtained from the Bounded Real Lemma and LMI region characterization. Simulations are conducted for several types of disturbances (sine, impulse, step, and random) and variations (slow and abrupt) of mass and moments of inertia. The reference path (sine, impulse, and step) is well-followed showing the ability of the design method to handle different performance objectives.

International audience; Lateral velocity and tire-road forces are vital signals that affect the stability of a vehicle under cornering. Unfortunately, for both technical and economic reasons, these fundamental vehicle parameters can hardly be measured directly through sensors. As a consequence, an efficient and reliable algorithm for estimating vehicle lateral velocity and tire-road forces is needed. This paper presents a novel framework for estimation of vehicle lateral velocity and lateral tire-road forces. The proposed algorithm is based on switched interval observers and is able to cope with changes of tire operating conditions. The interval estimation algorithm is evaluated through experimental data acquired using an instrumented vehicle. Simulation results show that the developed system can reliably estimate the upper and lower bounds of vehicle lateral variables during both steady and transient maneuvers.

International audience; This paper investigates the problem of robust state estimation and unknown input interval reconstruction for uncertain switched linear systems. Parameters uncertainty are supposed to be provided with known bounded compact set. A design method for obtaining interval observers that provide guaranteed lower and upper bounds of the state and unknown inputs is proposed. By adopting multiple quadratic ISS-Lyapunov function and average dwell time concept, new and less conservative stability conditions are derived, and a set of numerical feasible linear matrix inequalities (LMIs) are given. An application to vehicle lateral dynamics estimation is considered to show the effectiveness of the algorithms. Experimental data obtained with a prototype vehicle are used to confirm the performance of the proposed approach.

The objective of this study is the analysis of dynamic systems represented by multi-model with variable parameters. Changes in these parameters are unknown but bounded. Since it is not possible to estimate these parameters over time, the simulation of such systems requires to consider all possible values taken by these parameters. More precisely, the goal is to determine, at any moment, the smallest set containing all the possible values of the state vector simultaneously compatible with the state equations and with a priori known bounds of the uncertain parameters. This set will be characterized by two trajectories corresponding to the lower and upper limits of the state at every moment. This characterization can be realized by a direct simulation of the system, given the bounds of its parameters. It can also be implemented with a Luenberger type observer, fed with the system measurements.

International audience; This study addresses the problem of guaranteed state and unknown input (UI) estimation for a class of linearparameter varying systems affected by UIs and other bounded perturbations. The context of interval observer in the cooperativeframework is adopted. Thus, lower and upper bounds of the state and UI are provided. No assumption is made on the UI. Theapproach is based on a rank condition allowing to decouple the UI from the state estimation errors (so that the state estimationis guaranteed, regardless of the variation of the UI). The convergence of the proposed interval observer is studied by Lyapunovtheory and stability conditions are expressed in terms of linear matrix inequalities which ease the design of the gain matrices ofthe observer. Finally, illustrative examples are given for discussion and comparison with respect to the existing results.

International audience; In this paper, the problem of unknown input observer (UIO) design for nonlinear parameter varying (quasi-LPV) systems is investigated. Three main improvements of the existing UIO designs for LPV systems cite{Marx2019} are detailed. First, the parameter dependency of the UIO is not restricted to be the same as the one of the system, then the existing decoupling conditions are relaxed. Secondly, the class of considered systems is nonlinear which leads to the well-known quasi-LPV systems (i.e. the parameters are state dependent). This paper focuses on the case of parameters depending on unmeasured states. Finally, the proposed UIO considers the cases when only estimated time derivative of the parameters is available, and also unavailable time derivative and estimation. For these cases, the Disturbance-to-Error Stability (DES) is considered with DES-gain optimization. Examples are provided to illustrate the performances of the proposed UIO designs and highlight the improvements brought to existing ones.

International audience; Functional interval observer of dynamical switched systems provides significant advantages in practical applications. In view of the enlarged order of interval observers, applying interval functional observers can result in lower computational costs and more practicability in some applications such as output feedback control and fault diagnosis of these systems. In this paper, an unknown input functional state interval observer design for a class of switched uncertain systems is investigated. Necessary and sufficient conditions for observer existence are derived. Based on Input to State Stability (ISS) principle and Lyapunov theory, the stability and positivity conditions for the estimation errors are expressed in terms of Linear Matrix Inequalities. A design procedure algorithm of the state observer is given. Finally, the proposed estimation methodology is applied to vehicle lateral velocity estimation problem. Simulation results obtained, confirm the good accuracy and robustness of the proposed state estimation concept.

International audience; This paper investigates the design of interval observer for switched uncertain systems with bounded uncertainties that appear in both the state and output equations. The proposed observer provides an envelope covering all possible state trajectories. By means of multiple ISS-Lyapunov function as well as linear matrix inequalities formulation, the interval observer gain matrices are determined and sufficient conditions ensuring the Input-to-State Stability (ISS) of the estimation error are proposed. An application for vehicle lateral dynamics estimation is presented to evaluate the performance of the proposed algorithm. The interval observer is applied to estimate the sideslip angle in the presence of uncertain tire cornering stiffness parameters and time-varying vehicle longitudinal velocity. The obtained observer is evaluated using experimental data acquired with a prototype vehicle. The simulation results demonstrate the validity of the proposed design.

This paper investigates the construction of an interval observer for bilinear systems with unknown inputs and affected by bounded perturbations. The observer is made such that the interval error bounds are independent from the unknown inputs. Conditions for an asymptotic boundedness, as well as practical design considerations are given. Finally, an example illustrates the theoretical contribution.

This paper focuses on the design of new observers for Discrete-Time Switching Systems with Unknown Inputs (UI). The particularity of the present paper in comparison with the existing works from the literature is to consider the switching sequence as totally unknown. After, stating some assumptions, a first state observer is proposed in the noise-free case. Then, based on this former one, another state observer is proposed for systems perturbed by bounded noises. In both cases, results on the observer convergence are given. Finally, an example illustrates the theoretical contributions.

International audience; This paper presents an observer based sensor faultdiagnosis for 2-D systems. Firstly, a state observer is designed bytaking into account the measurements in a fixed length slidingwindow. Secondly, structured residual signals are generated bya bench of finite memory state observers which allow to detectand isolate sensor faults affecting the system. Finally, simulationresults are given to illustrate the proposed approach.

This paper investigates the construction of an interval observer for nonlinear Lipschitz systems with unknown input. The nonlinear part of the considered system is made by a Lipschitz function. The idea of the proposed observer is to use the derivative of the output vector in order to decouple the unknown input from the interval error bounds. After recalling the useful assumptions, the observer is constructed and the interval error are proved to be asymptotically bounded. Finally, an example illustrates the theoretical contribution.

International audience; In this paper, the problem of observers for Takagi-Sugeno (TS) models with unmeasurable premise variables is investigated and a new design approach is proposed. The idea, is motivated by the immersion techniques and auxiliary dynamics generation, and consists in the transformation of the TS system with state dependent weighting functions in a new TS system with weighting functions depending only on the measured variables. This result aims to relax the strong conditions used in the design of observers for TS systems with unmeasurable premise variables. Illustrative examples are provided to discuss the performances of the proposed approach.

Process monitoring needs the development of data analysis tools aiming at recognizing, at each time instant, system operating mode using the measurement collected on the system. This communication aims at presenting a method relying on measurement analysis, able to identify operating modes without the knowledge of the mathematical models describing these modes. The proposed method relies on the writing of a global model combining, in a multiplicative way, the models describing the different modes. The parameters of this global model are then numerically identified from the available set of measurements. The sensitivity analysis of the global model with regard the input/output variables then provides an indicator to identify, at each instant, the current operating mode. The proposed method is applied on a simplified model of a grinding mill.

Summary This paper presents a new scheme for sensor fault tolerant control for nonlinear systems based on the Takagi–Sugeno modeling. First, a structured residual generator aimed at detecting and isolating sensor faults is designed. A bank of observers controlled either by only one system output or a set of outputs is then implemented, leading to a set of state estimates. The parallel distributed compensation structure is adopted to design the fault tolerant controller. The novelty in this paper is that the estimated state used in the controller is a weighted state vector obtained from all the estimated states provided by the different observers. The weighting functions depend on the residual vector signals delivered by the residual generator. They are designed to avoid crisp switches in the control law. Indeed, the interesting feature of the proposed approach is to avoid the commonly used switching strategy. For each residual component, the greater its magnitude is, the less the weight affected to the corresponding state estimate is. Consequently, the controller only uses estimations computed on the basis of healthy measurements. The closed-loop stability is studied with the Lyapunov theory, and the obtained conditions are expressed as a set of linear matrix inequalities. The proposed residual generation and fault tolerant controller are applied to a vehicle lateral dynamics affected by sensor faults. Copyright © 2015 John Wiley & Sons, Ltd.

International audience; The flatness-based approach is presented in this paper in order to estimate the motorcycle lateral dynamics such as the roll angle, the lateral tire forces or the steering torque from basic measurements. The model of the motorcycle associated with the flatness theory are used to express the unknown states and input in terms of nonlinear functions depending only on the measures and their time derivatives up to a given finite order. These time derivatives are estimated via a non-asymptotic differentiator. Finally, the ability of the proposed observer to estimate the motorcycle dynamics is illustrated through two simulation scenarios performed with the well-known motorcycle simulator”BikeSim”.

In this work, two high order sliding mode observers under cascade form are proposed in order to estimate the important states and inputs affecting the lateral dynamics of two-wheeled vehicles. The first observer is based on a vision system and is used to estimate the lateral velocity of the vehicle. This velocity is considered as an additional measure for the second observer which is designed to estimate the tire forces, the roll angle and torque applied to the handle-bar. The main contribution of this work is the estimation of the tire forces even with the variation of the longitudinal velocity and without the prior knowledge of the pneumatic coefficients.

In this paper the design of observer under the presence of unknown inputs for linear parameters varying transportation systems is considered. The main idea consists in getting a set of conditions to design an observer, which estimates a part of the motorcycle dynamics states independently of some inputs (rider torque) and/or other states (zeros dynamics: roll angle) taken into account the variation of the longitudinal velocity. The observer design conditions for this new representation are expressed as LMI constraints. The effectiveness of the proposed observer is illustrated on motorcycle dynamics state estimation.

International audience; This paper addresses a new scheme for fault diagnosis in nonlinear systems described by Takagi-Sugeno multiple models. Two cases are considered, the first one concerns the T-S models with known premise variables (the input or the output of the system). For the second case it is supposed that the weighting functions depend on unmeasurable premise variables (state of the system). The approach is based on the design of observer-based residual generator by minimization of the disturbances effect and maximizing the effects of the faults. The synthesis is based on the L2 formalism developed for linear systems. The convergence conditions are given in LMI formulation.

International audience; In this paper, we present a new method for the computation of the maximal authorized motorcycle speed in curves. The three main actors which are the vehicle, the driver and the infrastructure are taken into account. The vehicle dynamics are represented by a dynamic four degrees of freedom model which includes the vehicle's longitudinal slip and side slip angle. The driver behavior model considers his ability in deceleration maneuvers according to the mobilized friction. The infrastructure characteristics introduce a precise handling of the road geometry and of the maximal available friction.

International audience; In this paper, the problem of observer design for nonlinear Lipschitz systems is treated. An emphasis is put on maximizing the admissible Lipschitz constant for which the observer design is possible. This problem is tackled using a Takagi-Sugeno modeling approach. The idea is to re-write the state estimation error dynamics as an autonomous Takagi- Sugeno system, using the Mean Value Theorem and the sector nonlinearity transformation. The stability of the state estimation error is studied with the Lyapunov theory by using a non- quadratic Lyapunov function and by computing its variation between m consecutive samples. The interest of these manip- ulations is to obtain LMI conditions admitting solutions for large values of the Lipschitz constant. Finally, two examples are provided in order to hilight the performances of the proposed approach.

International audience; This paper deals with the problem of observer design for vehicle lateral dynamics. The nonlinear model of this last is transformed into Takagi-Sugeno (T-S) formulation by using the sector nonlinearity transformation. The main contribution of this paper is the representation of the vehicle nonlinear model by a T-S model with minimal loss of information (almost exact T-S model). This inevitably leads to a model with unmeasurable premise variables which is more difficult to study compared to the classical T-S models where premise variables are assumed to be measurable even if this is not really true as their are often estimated. The second contribution of this paper is the observer design for estimating the lateral dynamics of the vehicle. Stability conditions are established using a Lyapunov method and the concept of Input-To-State Stability (ISS). These conditions are then expressed in terms of optimization problem subject to LMI constraints. Simulation results are provided to illustrate the proposed approach, where the observer is synthesized with a T-S model and then applied directly to the nonlinear model of the vehicle. Some aspects of the robustness of the observer, with respect to time varying longitudinal velocity and measurement noise, are discussed.

This paper proposes a trimodal model of urban traffic for controlling the traffic policy. A model predictive control is then designed. The model focuses on the general traffic (private vehicle and bus) mode and BRT (Bus Rapid Transit) mode. An innovative model is presented for both the BRT mode, the private vehicles mode (VP) and for the Buses mode. The model is essentially based on the TUC (Traffic-responsive Urban Control) strategy. Based on this model, a predictive control is presented by minimising a cost function in order to control the urban traffic. The effectiveness strategy is illustrated by simulation results.

International audience; This paper addresses a new methodology to con- struct a fault tolerant control (FTC) in order to compensate actuator faults in nonlinear systems. This approach is based on the representation of the nonlinear model with a multiple model under Takagi-Sugeno's form. The proposed control requires a simultaneous estimation of the system states and of the occurring actuator faults. The performance of the control depends on the quality of the estimations, indeed, it is important to estimate accurately and rapidly the states and the faults. This task is then performed with an Adaptive Fast State and Fault Observer (AFSFO). The stability conditions are established with Lyapunov theory and expressed in linear matrix inequality formulation to ease the design of the FTC. Furthermore, relaxed stability conditions are given with the use of the Polya's theorem.

International audience; This paper presents a new method for fault tolerant control of nonlinear systems described by Takagi- Sugeno fuzzy systems with unmeasurable premise variables. The idea is to use a reference model and design a new control law to minimize the state deviation between a healthy reference model and the eventually faulty actual model. This scheme requires the knowledge of the system states and of the occurring faults. These signals are estimated from a Proportional-Integral Observer (PIO) or Proportional-Multi- Integral Observer (PMIO). The fault tolerant control law is designed by using the Lyapunov method to obtain conditions which are given in Linear Matrix Inequality formulation (LMI). Finally, an example is included.

This paper deals with state estimation of Powered Two Wheeled vehicle (PTWV) and robust reconstruction of related unknown inputs. For this purpose, we consider a unknown-input high order Sliding-mode observer (UIHOSMO). First, a motorcycle dynamic model is derived using Jourdain's principle. In a second time, we consider both the observation of the PTWV dynamic states, the reconstruction of the lean dynamics (roll angle φ(t)) and the rider's torque applied on the handlebar. Finlay, several simulation cases are provided to illustrate the efficiency of the proposed observer.