Hugues Mounier

Flatness-Based Vehicle Steering Control Strategy With SDRE Feedback Gains Tuned Via a Sensitivity Approach

This paper presents a feedback steering control strategy for a vehicle in an automatic driving context. Two main contributions in terms of control are highlighted. On the one hand, the automatic reference trajectories generation from geometric path constraints (obstacles). Thanks to the flatness property of the considered model, the longitudinal velocity will be controlled around a quasi-constant value while lateral and yaw dynamics targets will allow to avoid obstacles. On the other hand, a sensitivity-based methodology will be presented to choose the best possible gains parameterization in a state Riccati dependent equation (SDRE) feedback controller. Both direct and adjoint sensitivity methods are used, together with a dynamic inversion of the system, in order to optimize the performances of the controller. Obstacle avoiding simulation results will be validated and compared with other nonlinear optimal feedback controllers, from a realistic industrial simulator environment for vehicle dynamics

Tracking Control and π-Freeness of Infinite Dimensional Linear Systems

This is a report on recent works [1, 17, 19, 20, 21, 39, 40, 41, 43] on the control tracking of some infinite dimensional linear systems. It is based on a new property, called π-freeness, which allows the tracking of a reference trajectory in a way which bears some analogy with flat finite dimensional nonlinear systems (see [15, 16] and the references therein). Several examples are examined and simulations are provided.

Flatness-based control of nonlinear delay systems: A chemical reactor example

A trajectory tracking control method for a class of non-linear systems with time delays is proposed. For this, the new concept of delta-flatness is introduced, which is an extension of the notions of flatness for non-linear systems and delta-freeness for linear delay systems. A two-step design procedure is derived. It splits into trajectory design, which directly provides an open-loop tracking controller, and stabilization around the reference trajectory. This feedback stabilization is based on a state prediction, leading to a discrete time controller.

Theory and Practice in the Motion Planning and Control of a Flexible Robot Arm Using Mikusiński Operators

Abstract The motion planning and the synthesis of a tracking controller of a flexible robot arm is studied in an algebraic framework using Mikusinskis operational calculus. Experimental results are reported.

A distributed parameter approach to the control of a tubular reactor: a multivariable case

The start-up and the shutdown of tubular fixed-bed reactors can be improved by an explicit trajectory design and active control. By using the inflow concentration as a control the outflow concentration can be changed in arbitrary finite time. Explicit series expansions of the control inputs are calculated using the distributed parameter system model. It is shown that these promising techniques are not restricted to the single-input case, but can easily be extended to certain multivariable models. The control laws derived are new in the scalar case.

Robust stop-and-go control strategy: an algebraic approach for non-linear estimation and control

This paper describes a robust stop-and-go control strategy for vehicles. Since sensors used in a real automotive context are generally low cost, measurements are quite noisy. Furthermore, many vehicle/road interaction factors (road slope, rolling resistance, aerodynamic forces) are very poorly known. Hence, a robust strategy to noise and parameters is proposed within the same theoretical framework: algebraic non-linear estimation and control techniques. On the one hand, noisy signals will be processed to obtain accurate derivatives, and thereafter, variable estimates. On the other hand, a grey-box closed-loop control will be implemented to reject all kinds of disturbances caused by exogenous parameter uncertainties.

Path Planning using a Dynamic Vehicle Model

This paper addresses the problem of path planning using a dynamic vehicle model. Previous works which include a basic kinematic model generate paths that are only realistic at very low speed. By considering higher vehicle speed during navigation, the vehicle can significantly deviate from the planned trajectory. Consequently, the planned path becomes unusable for the mission achievement. So, to bridge a gap between planning and navigation, we propose a realistic path planner based on a dynamic vehicle model

Algebraic interpretations of the spectral controllability of a linear delay system

Abstract Interpretations of several existing results on spectral controllability of a linear delay system are given. A general characterization in a recently proposed module theoretic framework is presented. This setting enables a clear and precise comparison of the various examined notions.

Controllability of Networks of Spatially One-Dimensional Second Order PDEs—An Algebraic Approach

We discuss controllability of systems that are initially given by boundary coupled PDEs of second order. These systems may be described by modules over particular rings of distributions and ultradistributions with compact support arising from the solution of the Cauchy problem of the PDE under consideration with data on the time axis. We show that those rings are Bezout domains. This property is utilized in order to derive algebraic and trajectory related controllability results.

Estimation of longitudinal and lateral vehicle velocities: An algebraic approach

This paper presents a new approach for estimating vehicle velocities at its gravity center. The proposed strategy relies on recent algebraic techniques for numerical differentiation and diagnosis. We do not use any tire model in order to obtain an estimation, which is robust with respect to model uncertainties (friction, ...). All available measurements in a mass-production car are however exploited.