The stability of the mold level in continuous slab casting machines is an important factor determining the final quality of flat carbon steel.The existing performant feedback control system of Slab Caster 2 in the Steel Shop of ArcelorMittal Gent will be extended with a feedforward signal using the predicted mold level.A prediction algorithm, an early warning detection system and detailed FFT analysis of the mold level variations have been designed in MATLAB-Simulink. PLC code is generated directly from the MATLAB design, and will be implemented in a PLC serving as PROFINET I-Device in the base automation of slab caster KG2.

The revamping of a machine manufacturer's line of high speed processing machines aims to reuse existing validated STEP 7 code. The distributed networked sensing architecture is required to pick out a single analog measurement with 50 ps resolution at specific encoder sample hits, using off-the-shelf PROFINET I/O. A solution using an oversampling technique on a remote I/O device combined with a low-cost “streaming CPU” running in isochronous processing mode and acting as sync master in PROFINET IRT is proposed. The distributed architecture connects a main CPU to the streaming CPU, the latter configured as I-Device in a 2ndPROFINET RT network. Overall distributed architecture, accurate reconstruction of the signal timing, network load and the signal propagation are analysed.

This paper briefly discusses the design of a low-cost, versatile and configurable error generator for PROFIBUS DP. Using a PROFICORE ULTRA oscilloscope trigger pulse, a small circuit designed around an Arduino MEGA 2560 disrupts messages on the industrial network, without adding an extra slave.

Due to its high potential and encouraging results, project-based learning emerges as a highly interesting paradigm in the education systems worldwide. Moreover, robotics is an interdisciplinary field where students could learn and apply their skills in mechanics, electronics, computer science, mathematics and control engineering. This paper presents a robotics project-based learning methodology which focuses on collaborating with the industry to design, develop, evaluate, integrate and manage projects designated to be used in real-life applications. This learning method emphasizes and enables the students to apprehend the importance of fulfilling client requirements and the interactions with the client, the suppliers and with the other members of the team. The students, coached by a partner from industry, have the opportunity to apply and to improve their project management skills under a large-scale, highly complex project. This method is being applied since 2008 at ISEN Lille, France, with good results and significant impact.

A single landmark based localization algorithm for unicycle mobile robots was provided in [1]. It is based on the algebraic localizability notion and an efficient differentiation algorithm in noisy environment ([2], [3]). Let us stress that this localization algorithm do not need to know the linear and the angular velocities which are reconstructed by this algorithm using the kinematic model. In this paper, a sensibility study leads to a new fusion algorithm in the multi landmark case using as a basis our posture differentiation based estimator. Some simulations and experimental results are presented in order to prove the effectiveness of the proposed method compared to the well known EKF method.

This paper proposes a single landmark based localization algorithm for non-holonomic mobile robots. In the case of a unicycle robot model, the localization problem is equivalent to the system observability. Based on this observation, the proposed localization method consists in finding a vector function which depends on the measurement vector and its derivatives. In order to compute estimates of the successive derivatives of the measurement vector, we will use a numerical differentiation method. When the robot is able to only measure the relative angle between itself and the landmark in 2D case, the algorithm estimates the posture of the robot, under the hypothesis that control inputs are known. But, sometimes it is also useful to be able to estimate the control input (for example when the robot slips). This is possible with the proposed algorithm by using a landmark in dimension three. The simulation results will be given in order to show the effectiveness of the proposed algorithm. Moreover, these results are compared with those obtained by an Extended Kalman Filter in order to underline the advantages of the new algorithm.

This paper presents an architecture for the navigation of an autonomous mobile robot evolving in an uncertain environment with obstacles. The proposed strategy consists in separating the path planning from the control algorithm. The path planning is done by computing the time optimal collision-free trajectory which takes into account the limitations on the linear and angular speeds of the vehicle. The position and shape of obstacles are computed by a vision algorithm using a single camera. A saturated controller based on integral sliding mode is designed to solve the tracking problem in the presence of input saturations and of the unknown disturbances. The effectiveness, perfect performance of obstacle avoidance, real-time and high robustness properties are demonstrated by experimental results.

This paper presents a closed form solution for the dynamic model of a parallel robot. This robot is utilized like a haptic interface for a surgical simulator used in the amnicentesis operation. The dynamic model is obtained by using the Lagrange formulation applied to parallel robot. It is proved that for a large class of parallel robots which has some properties, it is possible to avoid the explicit calculation of Lagrange multipliers. The aim is to simplify the calculation for a real-time application.