Malik Loudini

Modelling and Intelligent Control of an Elastic Link Robot Manipulator

In this paper, precise control of the end-point position of a planar single-link elastic manipulator robot is discussed. The Timoshenko beam theory (TBT) has been used to characterize the structural link elasticity including important damping mechanisms. A suitable nonlinear model is derived based on the Lagrangian assumed modes method. Elastic link manipulators are classified as systems possessing highly complex dynamics. In addition, the environment in which they operate may have a lot of disturbances. These give rise to special problems that may be solved using intelligent control techniques. The application of two advanced control strategies based on fuzzy set theory is investigated. The first closed-loop control scheme to be applied is the standard Proportional-Derivative (PD) type fuzzy logic controller (FLC), also known as PD-type Mamdanis FLC (MPDFLC). Then, a genetic algorithm (GA) is used to optimize the MPDFLC parameters with innovative tuning procedures. Both the MPDFLC and the GA optimized FLC (GAOFLC) are implemented and tested to achieve a precise control of the manipulator end-point. The performances of the adopted closed-loop intelligent control strategies are examined via simulation experiments.

A real-time feedback scheduler for environmental energy with discrete voltage/frequency modes

This paper, addresses the problem of real-time scheduling in ambient energy harvesting systems with discrete voltage/frequency modes through the use of a feedback scheduler. The main idea explored in this paper is to reduce the processor speed in proportion to the amount of available energy and processor load. The evaluation of this new real-time feedback scheduler shows experimentally a good compromise between the available energy and the processor workload, and allows a progressive selection of processor speeds. In this work, we compare several battery thresholds knowing that the processor performs the tasks at maximum speed when the battery storage is over the thresholds.

Incorporate intelligence into the differentiated services strategies of a Web server: an advanced feedback control approach

This paper presents an investigation into the application of advanced feedback control strategies to provide better web servers quality of service (QoS). Based on differentiated service strategies, fuzzy logic based control architectures are proposed to enhance the system capabilities. As a first control scheme, a Mamdani fuzzy logic controller (FLC) is adopted. Then, the Simulated Annealing (SA) algorithm (SAA) is used to optimize the FLC parameters with efficient tuning procedures. The SA optimized FLC (SAOFLC) is also implemented and applied to improve the system QoS. Simulation experiments are carried out to examine the performances of the proposed intelligent control strategies.

Car-like mobile robot navigation in unknown urban areas

This paper implements an automated transportation system allowing passengers on a car-like robot to reach their destination safely, intelligently and autonomously. Different components of the system are described such as localization based on Hector SLAM, humans detection based on HOG (Histograms of Oriented Gradient) descriptor and intelligent navigation based on FNN (Fuzzy neural networks) approach. To show the whole system effectiveness for the car-like mobile robot Robucar, experimentations were done in ROS, in an unknown human environment.

Comparative study of maximum power point tracking methods of photovoltaic systems

The aim of the present research is the comparative for variety controller of maximum power point tracking (MPPT) in photovoltaic system under variable temperature and isolation conditions. The first controller refers to traditional approach based on the perturbation & observation (P&O) methods, the second and third one refers to new approach based respectively on artificial neural network (ANN) and fuzzy logic (FC). The performances of these adopted controllers are examined and compared through a series of simulation witch shown the good tracking and rapid response to change in different meteorological conditions of intelligent controllers compare with the conventional one.

RTSBL: Reduce Task Scheduling Based on the Load Balancing and the Data Locality in Hadoop

We address load balancing and data locality problems in Hadoop. These two problems limit its performance, especially, during a reduce phase where the partitioning function assigns the keys to the reducers based on a hash function. We propose in this paper a new approach to assign the keys based on the reducers’ processing capability in order to ensure a good load balancing. In addition, our proposed approach called RTSBL takes into consideration the data locality during the partition. Our experiments prove that RTSBL achieves to up 87% improvements in the load balancing and 3\(\times \) improvements of the data locality during the reduce phase in the standard Hadoop.

Active queue management exploiting the rate information in TCP-IP networks

In this paper, we propose a new mechanism called explicit rate notification U+0028 ERN U+0029 to be used in end-to-end communications. The ERN scheme encodes in the header of transmission control protocol U+0028 TCP U+0029 packets information about the sending rate and the round trip time U+0028 RTT U+0029 of the flows. This new available information to the intermediate nodes U+0028 routers U+0029 is used to improve fairness, increase utilization, decrease the number of drops, and minimize queueing delays. Thus, it induces a better management of the queue. A comparison of our scheme with preexistent schemes, like the explicit congestion notification scheme, shows the effectiveness of the proposed mechanism.

ERN: Explicit rate notification AQM for TCP-IP networks

Active Queue Management (AQM) tries to find a balance between keeping high link utilization, minimizing queueing delays, so as not to introduce unnecessary end-to-end delays, and ensure a fair share of bandwidth between flows. Traditional AQM mechanisms have been built using only information that are present in routers, and it is quite understandable given the importance of the scaling-up property, which is quite fundamental to mechanisms governing the networks. In this paper, we propose a new mechanism called Explicit Rate Notification (ERN) to use in end-to-end nodes. The ERN scheme sends information about the sending rate and round trip time (RTT) of the flows. This new available information to the intermediate nodes (routers) is used to improve fairness, increase utilization, and minimizing queueing delays. Thus, it induces a better control of the queue. A comparison of our scheme with pre-existent schemes, like ECN, show the superiority of the proposed mechanism.

A real-time feedback scheduler based on control error for environmental energy harvesting systems

This paper addresses a real-time scheduling problem inherent to energy harvesting real-time systems. Traditionally, the energy saving problem is solved mainly by taking into account the tasks scheduling parameters such as worst-case execution time and period. In this work, we construct a feedback control scheduling scheme in which a discrete processor speed is assigned according to the control error and available energy. The real-time control tasks would get high processor speeds when their control errors increase. The experimental evaluation of this solution verifies that the feedback scheduling system based on control error gives a good compromise between available energy and systems performance.

A Real-Time Feedback Scheduler for Environmental Energy with Discrete Voltage/Frequency Modes

This paper, addresses the problem of real-time scheduling in ambient energy harvesting systems with discrete voltage/frequency modes through the use of a feedback scheduler. The main idea explored in this paper is to reduce the processor speed in proportion to the amount of available energy and processor load. The evaluation of this new real-time feedback scheduler shows experimentally a good compromise between the available energy and the processor workload, and allows a progressive selection of processor speeds. In this work, we compare several battery thresholds knowing that the processor performs the tasks at maximum speed when the battery storage is over the thresholds.