Toufik Bentaleb

This paper proposes kinematic based calibration methods for Delta parallel robots. The boundary of the robot workspace is computed using a forward kinematic model. Influence of errors in kinematic parameters on the workspace boundaries is investigated. The novelty of the proposed approach lies in...

This paper proposes a multivariable model predictive control scheme for discharge pressure regulation in centrifugal compressors. The main novelty of the proposed approach is that three control inputs are considered: the rotational speed of the compressor, an anti-surge valve for gas recycle and the inlet guide vane, whose variations allow one to significantly enlarge the operating region of the compressor and hence to enhance the authority of the control system. Surge prevention is achieved by including in the model an output variable accounting for the distance of the operating point from the surge limit. Such distance is defined on a compressor performance map which is invariant to changes in the inlet conditions, and thus its computation requires only standard pressure measurements available from the plant. Numerical simulations show that the proposed control system is able to meet the desired specifications, in the presence of different types of disturbances occurring along the pipeline.

This paper describes offline and real-time motion conversion approaches for imitating the motion of a human being using a humanoid robot. In both cases, the human motion is measured with marker points captured by the 3D motion capture system Vicon. A similar physical morphology between the shape of the robot and the human is assumed. This paper also demonstrates that the input measurements of the human motion to remain as close as possible to the real motion. In the offline approach, we use the iCub humanoid robot, while, for the real-time approach, James robot is used with some modification of the existing imitation and limiting human motion techniques. During the realisation of this work, we had a particular attention to obtain a 'natural' appearance of the motion. The proposed strategies, based on the obtained results, can be capable of accomplishing offline and real-time responses.

The objective of this paper is to develop a multivariable control system for a class of centrifugal compressors, which exploit as control signals both the rotational speed and the Inlet Guide Vane (IGV). Linear Quadratic Gaussian control with Integral action (LQGI) and Model Predictive Control (MPC) are investigated. The LQGI and MPC controllers are compared to a standard proportional integral (PI) controller, to regulate the discharge pressure of the compressor. The control algorithms are simulated and compared in different operating scenarios. Results demonstrate that the proposed multivariabe control schemes provide better performance than the single-loop PI controller, thus motivating the use of IGV for control purposes.

Industrial implementation of robots is to perform the assigned tasks in the minimum possible time in the cycle comes up to increase productivity and reduce the cost. The cycle time is strongly linked to the robot trajectory cycle to the task. However, the optimization of the robot trajectory cycle the robot visited a set of points which represent the robotics task. Similar to persons in traveling the robot execute the task into shorter time if has a shorter path. However the trajectory cycle of the robot is strongly related to the displacement in coordinate space rather than operational space. In fact, the shorter distance between two task points is the shorter distance between two configurations. Since robot has different configurations in each task point the minimum trajectory should be chosen between each successive configuration. However the order of visiting the task point also affects the trajectory distance. Moreover the relative robot position to the task also has a trivial effect on the task time. In this work we develop a method to optimize the order of visiting the task point taking into consideration the robot configuration and the placement of the robot in the robotized site. Mainly, this method is based on Genetic Algorithms and it takes into consideration the multiplicity solutions of the robot Inverse Kinematics Model (IKM), the task point visit order and the placement of robot at the same time.