In this work, we are interested to the PID control of nonlinear systems and more specially the control of a robot manipulator. The idea is to determine the optimal parameters (K p , K i and K d) of the controller using a novel algorithm of optimization called whale optimizer algorithm (WOA). To study the effectiveness of WOA-PID controller, its performance is compared with other controllers such as particle swarm optimization-PID (PSO-PID) and grey wolf optimizer-PID (GWO-PID). The model of robot manipulator and all controllers were tested using Simulink/MATLAB. Simulation results obtained clearly indicate the superiority of WOA-PID controller over the other controllers for trajectory tracking, better settling time, and ITAE errors.

No abstract

In this paper, we study the Covid 19 disease profile in the Algerian territory since February 25, 2020 to February 13, 2021. The idea is to develop a decision support system allowing public health decision and policy-makers to have future statistics (the daily prediction of parameters) of the pandemic; and also encourage citizens for conducting health protocols. Many studies applied traditional epidemic models or machine learning models to forecast the evolution of coronavirus epidemic, but the use of such models alone to make the prediction will be less precise. For this purpose, we assume that the spread of the coronavirus is a moving target described by an epidemic model. On the basis of a SIRD model (Susceptible-Infection-Recovery- Death), we applied the EKF algorithm to predict daily all parameters. These predicted parameters will be much beneficial to hospital managers for updating the available means of hospitalization (beds, oxygen concentrator, etc.) in order to reduce the mortality rate and the infected. Simulations carried out reveal that the EKF seems to be more efficient according to the obtained results.

This paper deals with macroscopic traffic modelling. It investigates real magnetic sensor data, provided by the Performance Measurements System (PeMS), in order to identify some traffic parameters related to a portion of the SR60-E highway in Califorina. Then, these parameters are used to validate a switched linear traffic model.

This study aims at presenting a hybrid Flexible Manufacturing System "HFMS" short-term scheduling problem. Based on the art state of general scheduling algorithms, we present the meta-heuristic, we have decided to apply for a given example of HFMS. That was the study of Simulated Annealing Algorithm SA. The HFMS model based on hierarchical Petri nets, was used to represent static and dynamic behavior of the HFMS and design scheduling solutions. Hierarchical Petri nets model was regarded as being made up a set of single timed colored Petri nets models. Each single model represents one process which was composed of many operations and tasks. The complex scheduling problem was decomposed in simple sub-problems. Scheduling algorithm was applied on each sub model in order to resolve conflicts on shared production resources