Computation of All Stabilizing PID Gain for Second-Order Delay System

The problem of stabilizing a second-order delay system using classical proportional-integral-derivative (PID) controller is considered. An extension of the Hermite-Biehler theorem, which is applicable to quasipolynomials, is used to seek the set of complete stabilizing PID parameters. The range of admissible proportional gains is determined in closed form. For each proportional gain, the stabilizing set in the space of the integral and derivative gains is shown to be either a trapezoid or a triangle

Multi-objective Optimization For The Dynamic Multi-Pickup and Delivery Problem with Time Windows

The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for multi-objective optimization of a dynamic multi pickup and delivery problem with time windows (Dynamic m-PDPTW). We propose a brief literature review of the PDPTW, present our approach based on Pareto dominance method and lower bounds, to give a satisfying solution to the Dynamic m-PDPTW minimizing the compromise between total travel cost and total tardiness time. Computational results indicate that the proposed algorithm gives good results with a total tardiness equal to zero with a tolerable cost.Comment: arXiv admin note: text overlap with arXiv:1101.339

A fast identification algorithm for systems with delayed inputs

International audienceA fast identification algorithm is proposed for systems with delayed inputs. It is based on a non-asymptotic distributional estimation technique initiated in the framework of systems without delay. Such technique leads to simple realization schemes, involving integrators, multipliers and piecewise polynomial or exponential time functions. Thus, it allows for a real time implementation. In order to introduce a generalization to systems with input delay, three simple examples are presented here. The first illustration is a first order model with delayed input and noise. Then, a second order system driven through a transmission line is considered. A third example shows a possible link between simultaneous identification and generalized eigenvalue problems

Online Implementation of Inequality Constraints Monitoring in Dynamical Systems

This paper deals with fault detection in dynamical systems where the state variables evolutions are constrained by inequality constraints. The latter corresponds either to physical limitations or to safety specification. Two classical residual generation approaches are studied, namely, parity space and unknown input observer approaches, and are extended to monitor the inequality constraints. A practical implementation on a real process is performed and permits to validate the relevance of the proposed methods

Online Implementation of Inequality Constraints Monitoring in Dynamical Systems

This paper deals with fault detection in dynamical systems where the state variables evolutions are constrained by inequality constraints. The latter corresponds either to physical limitations or to safety specification. Two classical residual generation approaches are studied, namely, parity space and unknown input observer approaches, and are extended to monitor the inequality constraints. A practical implementation on a real process is performed and permits to validate the relevance of the proposed methods

Identification algébrique du retard - Application à une soufflerie de séchage

Dans cette communication, on étudie l'identification en ligne du retard par l'approche algébrique. Une présentation de cette technique d'identification est effectuée. Une application à une soufflerie de séchage est envisagée. L'air est soufflé par un ventilateur tournant à une vitesse constante. Cette soufflerie est décrite par un modèle mathématique de type entrée-sortie, linéaire, continu, monovariable, du premier ordre, avec retard, opérant dans un cadre essentiellement stationnaire. Les résultats expérimentaux permettant de valider les résultats analytiques, sont présentés et commentés

Multi-Objective Optimization for the m-PDPTW: Aggregation Method With Use of Genetic Algorithm and Lower Bounds

The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers in purpose to satisfy precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for multi-objective optimization of a multi pickup and delivery problem with time windows (m-PDPTW), based on aggregation method and lower bounds. We propose in this sense a brief literature review of the PDPTW, present our approach to give a satisfying solution to the m-PDPTW minimizing the compromise between total travel cost and total tardiness time