Aziz Naamane

Model Splitting and First Order Sliding Mode Observers for Estimation and Diagnosis in Vehicle

Abstract In this paper a 16 Dof vehicle model is decomposed and used for partial state observation and some inputs estimation. The used sub-models are non linearly coupled and shown to behave well in application. Robust partial state observers with estimation of unknown inputs are developed using First Order Sliding Modes.

Generalized Discrete Event Abstraction of Continuous Systems: Application to an Integrator

In this paper we present our recent work on generalized discrete event modelling. In the general framework of modelling and simulation of linear systems under time-continuous – or not – signals, the description of the integrator operator becomes fundamental as well as the description the time delay operator and the concept of output feedback. Therefore, this paper shall present the description of an integrator under piecewise linear input trajectories in a first step, then under trajectories described by a sequence of general order polynomials, ensuring a user given accuracy. Moreover, its remarkable behaviour in case of input discontinuities strongly contrast with the rather bad one of classical numerical solvers. Furthermore, a thorough comparison with discrete-time simulation techniques, like the classical Euler one, allows the assessment of an important computational gain using the techniques proposed here. Finally, the complete treatment of an hybrid system example not only illustrates the relevance of this approach, but underlines the interest of its application in the more general context of mixed-mode simulation and distributed simulation.

Sliding modes observers for vehicle dynamics and variable structure automatic systems (SMO-VSAS)

This paper will show how to handle modeling of vehicles to get efficient and good Sliding Mode Observers. A car model with 16 DoF is decomposed for partial state observation with SMO. This decomposition method may lead, in VSAS, to good estimates of different kind variables and inputs (subsystems states, environment and ground variables, interfaces variables, connections and constraint variables). Robust Sliding Mode Observers and unknown input estimations are developed.

Sliding mode observer for estimation of all-terrain vehicle dynamic parameters

This paper uses sliding mode observers to build up an estimation of some unmeasurable parameters in all-terrain vehicle road interaction. An estimation of the angular velocity and acceleration is presented by using a second sliding mode observer. This estimation strategy is used to reconstruct the road slope. Also a fist sliding mode observer is developed to observe to road bank angle. To validate these approaches a experimentally data is used. The actual results show effectiveness and robustness of the proposed method.

Differential Estimators for State Observers in Vehicle Dynamics: HOSM and ALIEN

Abstract In this paper we compare robust differentiators to design observers to estimate the system state vector (HOSMO and ALIEN). We use for validation a driving simulator developed by Oktal. Robust partial state observers are developed for estimation using High Order Sliding Mode Observers and Algebraic approach (ALIEN * ).

Dynamic Modeling and Computer Simulation of 3D Objects Grasping

Among the essentials functionalities of several robotic systems are grasping and manipulating of objects by multi-fingered robot hands. Therefore many researchers have studied features of the two major closely related tasks.

Estimation of longitudinal tire forces for all-terrain vehicle

In this paper, an observer to estimate the longitudinal tire forces using only wheel angular positions measurement is presented. The robust estimation is based on Second Order Sliding Mode Observer. The estimation performance is tested and validated using a car driving simulator SCANeR™-Studio. The simulation results show effectiveness and robustness of the proposed method.

Sliding Modes Observers for vehicle dynamics and Structured Estimation (SE-SMO)

This paper show how to handle modeling of mobile robots or vehicles to get efficient Sliding Mode Observers and Structured Estimators of unknown inputs. To avoid observability problems the car model is decomposed for partial state robust observation. Finite time converging estimations are obtained with SMO. This decomposition method leads a Variable Structure System, giving good estimates of unknown inputs variables and environment parameters (subsystems states, environment and ground variables, interaction forces). Robust Sliding Mode Observers and unknown input estimations are developed.

Indirect field oriented control: A control strategy for electric wind power conversion

Different electric wind power conversion systems structures can be used based on the structures of converters used. The main objective in all topologies is always the same: the wind energy at varying wind velocities has to be converted to electric power with the highest performances [6,7,8,9,10]. In this paper a wind energy conversion schemes is presented based on the Indirect Field Oriented Control (IFOC)