Didier Aubry

Experimental Analysis of an Internet-Based Bilateral Teleoperation System With Motion and Force Scaling Using a Model Predictive Controller

This paper presents an experimental investigation of a bilateral generalized predictive controller for scaled teleoperation systems subject to slave force feedback, variable transmission-time delays, and packet losses. The originality of the approach proposed mainly lies in its capacity to take into account explicitly the slave force feedback in the predictive algorithm. Experimental results show the system stability with the proposed approach using a frequency-domain technique. Several configurations of scaling factors have been used; it is shown that the stability conditions strongly depend of the external environment. Another experimental result verify the robust performances of the approach in terms of tracking behavior with both strong variations of time delays and packet losses in the communication network. For the experimentations, the communication network is the Internet using user-datagram protocol, while the slave robot is a 6-DOF anthropomorphic robot with a force sensor.

Robust bilateral generalized predictive control for teleoperation systems

This paper presents a Generalized Predictive Control (GPC) extension, called Bilateral GPC (BGPC), for teleoperation systems in the presence of both communication delays and slave force feedback. The originality of the proposed approach is to take into account the case where the reference trajectory is not a priori known. This difficulty is due to the bilateral problem where the force feedback alters the reference trajectory. Some robustness properties are examined in the frequency domain showing the influence of a new prefllter in the BGPC structure. The proposed BGPC ensures robust stability of the closed-loop teleoperation system in the presence of environment and transmission time-delays uncertainties. Experimental results through a LAN (Local Area Network) are illustrated in this paper.

Finite Memory Observer for State Estimation of Hybrid System

Abstract Both industry and the academic world are becoming more and more interested in techniques to model, analyze, control and supervise complex systems that contain both analog and logical components. Such systems are called hybrid systems. This paper presents extensions and improvements on the finite memory observer. The main contribution is to incorporate the parity relation design and observer into a diagnosis scheme. The application of the finite memory observer to the sensor fault detection problem is illustrated by a numerical example. Simulation results show that the method is very effective for robust fault detection.

FAULT DETECTION OF A NONLINEAR SWITCHING SYSTEM USING FINITE MEMORY OBSERVERS

Abstract This paper is devoted to the design of a fault detection strategy for nonlinear switching discrete-time systems using Finite Memory Observers (FMO). Using both the past input/output measurements and the model equations, state estimation is expressed as a minimization problem of a cost function. Gauss-Newtons optimization method is investigated in a diagnosis purpose. Performances of FMO observers for residual generation on hybrid systems will be illustrated through numerical simulations on a benchmark two tank system.

Stability experiments of a scaled bilateral teleoperation system over Internet using a model predictive controller

This paper presents a control strategy based on a extension of the generalized predictive controller (GPC), called bilateral GPC, for scaled teleoperation systems in the presence of communication delays, packet losses and slave force feedback. The basic idea behind this approach is to take into account the case where the reference trajectory is not a priori known in a generalized predictive controller (GPC). This difficulty is due to the slave force feedback which alters the master reference trajectory. Experimental results show the overall system stability with the proposed BGPC approach using a frequency-domain technique. Several configurations of scaling factors have been used; it is shown that the stability conditions strongly depends of the external environment. Another experimental result verify the robust performances of the approach in terms of tracking behavior with both strongly variations of time-delays and packet losses in the communication network. For the experimentations, the communication network is Internet using UDP protocol while the slave robot is a 6-DOF anthropomorphic robot with a force sensor. The presented performance results have been obtained between two remote sites of a distance ap 1000 km.

Robust control for ultrasonic motor operating within harsh environments

Ultrasonic motor technology is a key system component in integrated mechatronics devices working on extreme operating conditions subjected to thermal cyclings or large thermal variations, EM disturbances, radiations, corrosion, or strong vibrations. Due to these constraints, robustness of the mechanics/electronics/control interfaces should be taken into account in the motor design. A robust controller for a travelling wave ultrasonic motor (TWUM) is considered in this study for operation in extreme environmental conditions. A simple causal model of the TWUM is introduced for identification of motor parameters. Then, an Hinfin loop shaping synthesis procedure is implemented in order to obtain a good compromise between environmental robustness and motors performances. Finally, simulation results demonstrate the effectiveness of the proposed robust controller in extreme operating conditions.

Indoor human/robot localization using robust multi-modal data fusion

Home automation is now implemented in many retirement homes in order to improve elderlys autonomy and safety. Smart homes allow to monitor the activities of elderly persons using information coming from different sensors. The ADL (Activities of Daily Living) are used to evaluate the ability of a person to perform on their own a selection of the activities which are essential for independent living in everyday life. The ADL are then used to detect deviations in a persons behaviour. Indoor localization based on the fusion of heterogeneous data from different sensors, is then essential for ADL characterization. For this purpose, a robust data fusion method is presented in this work through a multi-modal analysis to monitor the activities of elderly people (immobility, walking, etc) in a smart home. The paper describes the installation of sensors in a Living Lab and the preliminary experimental results using a set of Pyroelectric Infra Red (PIR) sensors, Radio Frequency Identification (RFID) distance measurement and the outcome of a noise analysis. Within a set-membership framework, our algorithm for robust localization employs a multi-modal data fusion approach dealing with faulty measurements.

DELAYED GENERALIZED PREDICTIVE CONTROL OF BILATERAL TELEOPERATION SYSTEMS

Abstract This paper presents a Delayed Generalized Predictive Controller (DGPC) by internal model for bilateral teleoperation systems in the presence of both communication delays and force feedback. First, the Π-freeness algebraic property of mechanical delayed systems, which presents some similarity with the notion of flatness, is used for the slave system to track a master system reference trajectory; the DGPC next ensures stability of the global slave system in spite of delays, disturbances or the slave force feedback (the reference trajectory is not a priori known). Simulation results illustrate the performance of the proposed predictive polynomial controller.

Experiments results on robustness effects of a new prefilter in generalized predictive control: Application to bilateral teleoperation systems

This paper presents experiments results of a generalized predictive control (GPC) extension, called bilateral GPC (BGPC), for teleoperation systems. The originality of the proposed approach is principally characterized by its capacity to take into account the slave force feedback in the predictive algorithm in order to ensure a better tradeoff between the robust stability of the closed-loop system and its transparency. This bilateral predictive controller introduces a new prefilter which plays a key role to enhance robust stability of the overall control system to the detriment of performances. In this paper, the effects of this prefilter will be shown through experiments results in time domain with a comparison to those obtained with a PID controller. The experimental setup on a LAN (local area network) is composed by PHANTOM Omni for the master and by a single degree of freedom translational mechanism for the slave.

Partial observer normal form for nonlinear system

In this paper, we investigate the estimation problem for a class of partially observable nonlinear systems. For the proposed Partial Observer Normal Form (PONF), necessary and sufficient conditions are deduced to guarantee the existence of a change of coordinates which can transform the studied system into the proposed PONF. Examples are provided to illustrate the effectiveness of the proposed results.