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PhD thesis: Control of nonlinear systems with algebraic constraints - application to cable robots taking into account the deformations of the cables

Description en Français

  • Context and objectives

Following previous works within the Control-Vision-and-Robotics group of ICube lab, this Phd subject is at the interface between control and robotics (refer to the projets IDRAC and ManiLPV). Indeed, we wish to contribute to the development of methods for system analysis and controller synthesis that suits for cable-driven parallel robots (CDPR). The developed methods should be as generic as possible while taking into account the specificities of the cable robots.

CDPR are composed of a platform connected to attachment points through cables whose length and tension are adjusted by winding. Their low invasiveness, large workspace and high load-mass-per-robot-mass ratio make them interesting solutions for original applications. ICube is already involved in the Dexterwide project that aims at developing a solution combining a serial arm embedded on a CDPR for performing drilling or welding tasks in construction halls. A demonstrator of INCA-6D, developed by the company Haption, is available in the laboratory for research.

The control of these systems has to face many complexities. On the one hand, as for all parallel robots, models exhibit algebraic equations in addition to dynamic equations - we speak of a differential algebraic equation (DAE), which represents a complexity to be managed for modeling and simulation. On the other hand, it must be ensured that the cable tensions remain positive. Moreover, they introduce flexible modes to the nonlinear dynamics of these systems which are also multivariable.

In previous works, we developed methods for model identification [NLC12, CCL16] and for the synthesis of correctors to control the platform in translation and rotation [CCL16]. In these works, the cables were supposed to be rectilinear, which made it possible to solve the algebraic equations.

  • Expected contributions

In this research work, the simplifying hypothesis of straight cables will be relaxed and the models will be processed directly in DAE form. A first contribution was produced by the team on the possibility of directly addressing the problem in DAE form for a simplistic example of plane robot with three straight cables [CL14]. In addition, a publication has just been accepted [ALP17] on taking into account the non-rectilinear character of cables in dynamics based on the "assumed mode" method commonly used for series manipulators with deformations [GPK97, HLB14]. This work can serve as a starting point for dealing with more complex robots. The approach will consist in approaching the nonlinear DAE model by a linear (also called "descriptor") or linear DAE model with variant parameters in order to use the methods available for these classes of systems [MKO97, Yag10]. The team had used this type of approach in the past for controlling arm manipulators series [HLB14]; It will be a question of transposing these approaches to parallel manipulators.

  • References
    • [ALP17] J.I. Ayala Cuevas, E. Laroche, O. Piccin, Assumed-mode-based dynamic model for cable robots with non-straight cables, Third International Conference on Cable-Driven Parallel Robots (CableCon2017), August 2-4, 2017, Quebec City, Canada
    • [CCL16] R. Chellal, L. Cuvillon, E. Laroche. Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots, International Journal of Control, pp. 1-18, 2016
    • [CL14] C. Cvetanovic, E. Laroche. Towards DAE methodology for the control of cable-driven parallel robots, dans IEEE Multi-Conference on Systems and Control, Antibes, France, October 2014.
    • [HLB14] H. Halalchi, E. Laroche, G. Bara. Flexible-link robot control using a linear parameter varying systems methodology, International Journal of Advanced Robotic Systems, Vol. 11(46):1-12, March 2014
    • [GPK97] H. Geniele, R.V. Patel K. Khorasani, End-point control of a flexible-link manipulator: theory and experiments, IEEE Transactions on Control Systems Technology, vol. 5, p. 556-570, 1997
    • [MKO97] I. Masubuchi, Y. Kamitane, A. Ohara, N. Suda, H∞ control for descriptor systems: a matrix inequalities approach, Automatica, vol. 33, no 4, p. 669-673, 1997
    • [NLC12] T. Nguyen, E. Laroche, L. Cuvillon, J. Gangloff, O. Piccin. Identification d’un modèle phénoménologique de robot à câbles, Journal Européen des Systèmes Automatisés, Hermès – Lavoisier, Vol. 56(6-7):673-689, November 2012.
    • [Yag10] M. Yagoubi, On multiobjective synthesis for parameter-dependent descriptor systems, IET Control Theory & Applications, vol. 4, No 5, p. 817-826, 2010
  • key-words:

Model based on algebra-differential equations, constrained system, linear parameter-varying system, cable-driven parallel robot

  • Applicant profile:

Student in second year of Master or in Engineer School in the last year with a strong specialization in automation, you are comfortable with the concepts of multivariable systems control and you use Matlab-Simulink without difficulty to implant models and To simulate them. You have a solid scientific base and you are comfortable with the mathematical tool. Your communication skills, especially in English, allow you to read scientific articles without difficulty understanding the language. You know how to be open-minded, you have the sense of initiative, while listening to the advice that is given to you. You know how to argue. You are able to demonstrate your ability to engage through your experiences.

Starting in October 2018

Location: ICube lab (Strasbourg south, Illkirch campus)

Funding: 3 year contract provided by the French Ministry of Higher Education

  • How to apply:

Send a resume, a cover letter that explains your skills with respect to the project and your motivations and your Master grades (use a unique pdf document) to homran@unistra.fr

Apply before: May, 15 2018

End of the session: June, 15 2018.

PhD : Identification of multivariable models for human-robot co-manipulation with passivity certificates

French version here

This PhD is part of a joint collaboration between ICube (Edouard Laroche), LIAS (Guillaume Mercère) and CEA (Neil Abroug). The location is at CEA-Saclay.

  • Context

Co-manipulation systems, also called cobots, are designed to interact with human operators physically in order to assist them in their work tasks. For instance, they provide force enhancement for handling or cutting tasks. Like any usual robotic systems, cobots are equipped with actuators and position sensors. Usually, they are also equipped with force sensors.

These robotic systems interact with uncertain and time-varying environments: on the one hand, with the operator who grips the handle more or less rigidly and, on the other hand, on the effector side, depending on the task it has to perform, either lifting a load of unknown mass or cutting an inhomogeneous material, to mention only simple cases. These environments are generally assumed to be passive: they only dissipate the energy provided to them. This property of passivity of the environment makes it possible to ensure the stability of the cobot in interaction with its environment, provided that it is itself passive.

Different approaches are available to identify a model of a robot. The so-called gray box methods rely on a model structure provided by the laws of physics, the parameters of which must be estimated. They result in passive models that are relatively compact and parsimonious, but have the disadvantage of not being able to easily encompass dynamics that are difficult to model physically but that can be crucial for the performance of the control. Black-box techniques (in the frequency domain with continuous-time models) are more suitable for obtaining powerful models for controller design in particular in the presence of flexible modes. However, the available methods are not able to ensure that the provided model is passive with satisfying accuracy.

  • Issue

In this thesis, methods will be developed for the identification of multivariable models from frequency data, that suit to the context of co-manipulation and with the goal of enabling the synthesis of robust control laws. The aim is to nicely combine the advantages of black-box and gray-box models to lead to passive representations capable of representing complex dynamics such as high frequency flexible modes. Experimental validation will be carried out on the demonstrators available at CEA-LIST.

  • Profile of applicant

This PhD proposal mainly requires skills in applied mathematics, automatic control and system identification more specifically. Fluency in French or in English is required. Thus, we are looking for candidates graduated from a Master of Science or an Engineering school with a solid scientific background with a specialization in control system theory and, of possible, in robotics. Your curiosity, your ability to analyze, your communication skills, as well as your commitment, will be a guarantee of success for the project.

  • Application

Please, provide:

- Curriculum Vitae and cover letter,

- Master marks,

- Certificate of proficiency in English,

A letter of recommendation will be appreciated. Any other document deemed necessary by the candidate which can enrich the application. Please send these documents to Neil.ABROUG@cea.fr, guillaume.mercere@univ-poitiers.fr and laroche@unistra.fr before April 27, 2018. In your cover letter, you must show your understanding of the subject and highlight your skills related to the topic. All documents will be provided in the form of a single pdf document whose title will be: NAME-Firstname-thesis-identifier-cobot.pdf.

Open Internship Positions within Project CAMMA

We are looking for motivated and talented students with knowledge in computer vision, machine learning and/or augmented reality who can contribute to the development of our computer vision system for the operating room.

Please feel free to contact Nicolas Padoy if you are interested to do your master's thesis or an internship with us (funding of ~500Euros/month will be provided during 3 to 6 months). The successful candidates will be part of a dynamic research group hosted within the IRCAD institute at the University Hospital of Strasbourg. They will thereby have direct contact with clinicians, industrial partners and also have access to an exceptional research environment. The CAMMA project is supported by the laboratory of excellence CAMI, the IdEx Unistra and the MixSurg Institute.

Topics:

  • Deep Learning for the Analysis of Large Surgical Video Databases
  • Multi-view Human Body Tracking for the Operating Room
  • 3D Simulation and Visualization of X-ray Radiations for Radiation Safety Analysis

More information about CAMMA

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