Complex Systems and Parsimony

The minimization of the ecological footprint of complex systems is the common denominator of this theme. Fugal mechatronic systems allow, by their original structure, to minimize the energy and raw material used for their manufacturing. Advanced control allows to minimize their energy consumption and their polluting emissions while making limited compromises on performance and robustness. Real-time embedded vision adds exteroceptive feedback to the control system to improve the accuracy and dynamic performance of lightweight mechanical systems.

Complex Systems

Event-Based Control

Sylvain Durand, sdurand@unistra.fr

Although periodicity simplifies the analysis in control theory, it results in conservative resource utilization because the control signal is computed, transmitted, and updated at the same rate, regardless of whether it is required or not. In contrast, the so-called "event-driven" paradigm exploits resources whenever they are truly needed. In such a novel framework, control updates are performed based on a triggering condition (e.g., when the dynamics of the controlled system or its environment change), resulting in sampling intervals that are no longer equidistant in time. The number of sampling instants can then be considerably reduced (compared to the periodic scheme) and, consequently, the computational usage and the network bandwidth. For all these reasons, event-triggered approaches offer opportunities for embedded cyber-physical systems with limited resources.

A new event-based control architecture was developed in the e-VISER ANR project context, with a complete event-driven sensorimotor chain from perception to actuation. Also, event-triggered control is investigated in the dark-NAV ANR project in the aim to develop new navigation strategies for UAVs in GPS-denied dark environment using aperiodic flash-based photolocation.

Control of Cobots

Hassan Omran, homran@unistra.fr
Bernard Bayle, bernard.bayle@unistra.fr
Edouard Laroche, laroche@unistra.fr 

We are interested in developing new methodologies for the control of collaborative robots (cobots) and the physical human-robot interaction. Our main focus is on using optimization-based methods, such as Model Predictive Control (MPC), which permits to impose a desired compliant behavior of the robot while respecting a set of safety constraints. We are also interested in integrating biosignals (electromyography) into the robot control strategy. This allows to obtain information about the human operator intentions and enhance the physical human–robot interaction dynamics.

Other topics in collaboration with CEA-LIST are:

• design of synthesis schemes for robust control of cobots, minimizing the transparency perceived by the operator (PhD of Neil Abroug)
• design of optimal excitation signals for identification of cobots that enable to finely identify the low-frequency flexible modes to be accounted for in the control scheme (also with LIAS, U. Poitiers) (PhD of Bassem Boukhebouz)

Control of nonlinear systems defined by algebro-differential equations

Edouard Laroche, laroche@unistra.fr 
Iuliana Bara, bara.iuliana@unistra.fr 
Hassan Omran, homran@unistra.fr
Olivier Piccin, Olivier.Piccin@insa-strasbourg.fr

The laws of Physics naturally appear as differential and algebraic (i.e. without any differential) equations, leading to so called DAE models. For controller design, the usual way is to first reduce the algebraic equations in order to get a minimal-order model composed of ordinary differential equations (ODE). However, this step has two drawbacks:

• It increases the complexity of the parameter dependence, and is therefore to the use of some methods for complex systems.
• The reduction step might be difficult to make (if not impossible) in a nonlinear context.

Moreover, a number of results are available in Control for analysis and controller design for descriptor models, i.e. linear DAE models.

Our research activities aim at developing methodologies for simulation, analysis and controller synthesis based on DAE models and exploit them for the control of complex systems. Our current activities consider planar cable-driven parallel robots that naturally exhibit algebraic equations coming from the mechanical closed-loop chains composed by the platform and the cables.

A Completer

Iulia, Florent

Parsimony

Flexible Mechanisms

Lennart Rubbert, lennart.rubbert@insa-strasbourg.fr
Marc Vedrines, marc.vedrines@insa-strasbourg.fr
Florent ?

Cable-Driven Parallel Robotics

Jacques Gangloff, jacques.gangloff@unistra.fr
Loïc Cuvillon, l.cuvillon@unistra.fr
Sylvain Durand, sdurand@unistra.fr
Edouard Laroche, laroche@unistra.fr

One specificity of Cable-Driven Parallel Robots (CDPRs) is that the rigid linkages of common parallel robots are replaced by cables. Using cables, CDPRs can achieve a high payload to robot mass ratio, large workspace, high-speed motion and cost effectiveness. However, the drawbacks inherent to cables are unilateral force — a cable can only pull and not push — and elasticity. Our team has studied the possibility of embedding additional actuators on the end-effector of a CDPR to actively correct these intrinsic weaknesses by the control. Moving masses and cold air thrusters have been studied as part of the DexterWide ANR project. Drone propellers have been studied during the eVISER ANR project.

Cable-driven manipulators are also considered as a challenging benchmark for control methodologies as they include several complexity sources: multivariable, non-linear with flexible modes and algebraic equations. See the section Control of nonlinear systems defined by algebro-differential equations below for details.

Aerial Manipulation

Jacques Gangloff, jacques.gangloff@unistra.fr
Loïc Cuvillon, l.cuvillon@unistra.fr
Sylvain Durand, sdurand@unistra.fr
Adlane Habed, habed@unistra.fr

The goal of the project dextAIR is to study the application of a new type of aerial manipulator using an elastic suspension. Nonlinear Model Predictive Control has been used to combine the computation of the optimal control input, the saturation management and the allocation of the control to the overactuated system. Elastic suspension from a CDPR has been studied within the eVISER ANR project. The goal of the STRAD ANR project is to develop an aerial manipulator based on the dextAIR concept for painting a huge street art mural. With the ANR TIR4sTREEt project, the goal is to use a dextAIR aerial manipulator to autonomously scan an urban area with climatology sensors.

Active Markers

Christophe Doignon, c.doignon@unistra.fr

Suivi et asservissement visuels à l'aide de la lumière structurée codée (Tracking and visual servoing with coded structured lighting). Sont plus spécifiquement ciblés, les systèmes embarqués (embedded systems) et légers. Quand ces systèmes sont articulés, la structure mécanique est très légère et le guidage précis des déplacements est un défi (challenge). Quant l'environnement dans lequel évolue ces systèmes exhibe des variabilités (de luminosité, de texture), voire qu'aucun indice visuel est perceptible par le capteur, des marqueurs artificiels matriciels embarquant de la redondance d'information sont projetés sur l'objet d'intérêt, avec un dispositif lui aussi embarqué. Des problématiques de recherche relevant du codage/décodage en temps réel de motifs numériques, du choix dynamique des indices visuels à projeter, du recalage et de la commande automatique sont alors étudiées dans ce cadre.

Knowledge/Vision Interaction

Adlane Habed, habed@unistra.fr