Samer Mansour

Online optimization of fuzzy-PID control of a thermal process

A constrained optimization of a simple fuzzy-PID (PID-proportional integral derivative) system is designed for the online improvement of PID control performance during productive control runs. The cost function design yields a desirable balance between rise time, setpoint overshoot, and settling time to the setpoint. The constraints determined by simulation yield control performance no worse than the existing control performance during online optimization. The optimized fuzzy-PID system is compared to a similarly optimized PID controller and a benchmark model predictive controller.

Wireless Sensor Network-based air quality monitoring system

This paper proposes a simple Wireless Sensor Network (WSN)-based air quality monitoring system (WSN-AQMS) for industrial and urban areas. The proposed framework comprises a set of gas sensors (ozone, CO, and NO2) that are deployed on stacks and infrastructure of a Zigbee WSN and a central server to support both short-term real-time incident management and a long-term strategic planning. This architecture would use open-hardware open-software gas sensing capable motes [6] made by Libelium. These motes use the ZigBee communication protocol and provide a real-time low cost monitoring system through the use of low cost, low data rate, and low power wireless communication technology. The proposed monitoring system can be transferred to or shared by other applications. We also introduce a simple but efficient clustering protocol dubbed hereafter “Clustering Protocol for Air Sensor network” (CPAS) for the proposed WSN-AQMS framework. CPAS proves to be efficient in terms of network energy consumption, network lifetime, and the rate at which data is communicated.

On simplified predictive control as a generalization of least-squares dynamic matrix control.

Simplified predictive control (SPC) of a single-input single-output control scheme is compared to the more sophisticated, least-squares formulation of dynamic matrix control (DMC) and its move-suppressed variant (move-suppressed DMC) for a typical two time-step control horizon. A closed-loop, continuous analysis shows that the discrete form of SPC generalizes the discrete DMC algorithm, and its variants, to control responses faster than one-half the process response time while remaining well conditioned.

Optimized K-Means Algorithm

The localization of the region of interest (ROI), which contains the face, is the first step in any automatic recognition system, which is a special case of the face detection. However, face localization from input image is a challenging task due to possible variations in location, scale, pose, occlusion, illumination, facial expressions, and clutter background. In this paper we introduce a new optimized k-means algorithm that finds the optimal centers for each cluster which corresponds to the global minimum of the k-means cluster. This method was tested to locate the faces in the input image based on image segmentation. It separates the input image into two classes: faces and nonfaces. To evaluate the proposed algorithm, MIT-CBCL, BioID, and Caltech datasets are used. The results show significant localization accuracy.

Tuning Proportional-Integral controllers to approximate simplified predictive control performance

An exact equivalence between PI (Proportional-Integral) and two-parameter SPC (Simplified Predictive Control) is developed to provide identical control of first order linear plants. A relationship between the PI control parameters and the SPC control parameters is described. This relationship that allows the same control in the case of first order linear plants is also found to provide tuning formulas that yield PI control which approximates SPC performance in the case of second order linear plants with widely separated Eigenvalues. Finally, an extension of the PI control algorithm to include future errors provides another exact PI-SPC equivalence for networked control of first order plants.

Risk aversion predictive control

A quality-controlled predictive control method, suitable for control of fast, remote systems subject to significant communication delays, is developed. Each move is quality controlled in that it independently satisfies a risk-based control performance criterion. The method is found to be capable of mitigating the ill effects of highly nonstationary delay distributions while providing good control performance for milder nonstationarity. It is demonstrated on simplified predictive control (SPC) of a single-input, single-output process. SPC is preferred here due to its simplicity and well-conditioned dependence of both the sampling time and its single parameter.

iCE: An Intelligent Classroom Environment to Enhance Education in Higher Educational Institutions

The intelligent Classroom Environment (iCE) promises to convey a rich and complex environment with the aim to achieve educational excellence and to provide world-class education in the university classroom environment. The classroom, the keystone for educational environments, is our first informational computer: a long-serving, complex, physical environment that embodies the education of human-minds; yet, classrooms are becoming an inadequate environment for tech-savvy generations. The iCE is a novel creative environment with the objective of enhancing education by embedding IT, Robotics, and Interactive Physical systems into the very fabric of the classroom’s design. The iCE communicates a unique and flexible setting that allows for a better educational environment. The iCE will be developed to reconfigure and retune six basic scenarios of the different tasks needed in contemporary classroom environments, calling them: the Exploration, Collaboration, Meeting, Lecturing, Lounging, and Presentation configurations. In this paper, we will present iCE’s concept, design, and iCE’s kinetic wall explorations, as scaled prototypes.

Centralized SON function for operator optimal strategies in heterogeneous networks

Recently emerging fourth generation networks, notably LTE-Advanced (LTE-A), are expected to meet the requirements of higher bit rates with excellent quality of service (QoS). The expansion and heterogeneity of these networks have made their operational cost higher, resulting in harder tasks for operators to remain competitive. Therefore, automatic engineering has recently been considered as a promising method in remote network management and human intervention minimization. Self-organizing networks (SONs) offer the possibility of remotely controlling the network in both pre-operational and operational states through self-configuration, self-optimization, and self-healing. In this paper, we propose a global handover self-optimization (HSOP) algorithm that jointly treats load balancing, energy saving, and ICI issues and can be deployed in a dynamic, automatic, and centralized way. Our proposed HSOP algorithm allows the mobile operator to choose the best HSOP strategy according to the network characteristics (place, time, user equipment type, and priority, etc.). Therefore, a traffic model must be available for the operator to indicate the input parameters of our global SON algorithm.

The Belonging Robot (BeRo): A Hybrid Physical-Digital System to Reflect Moods

The Belonging Robot or BeRo, is a hybrid physical-digital art installation to develop a culture of belonging, collaboration and connectedness of the students, the professors, and the employees to their educational institution. A mobile app and in-site sensory interactions relay the collective mood of these members to the physical system by changing the system’s physical configurations, in what we call the Belonging Robot (BeRo). BeRo’s users interact with its physical environment using pressure sensors in the form of five different colored buttons corresponding to the five different moods of users; or, the users may choose to have their inputs through a mobile app buttons of these different moods. BeRo’s configurations are to reflect the five selected moods: Very Satisfied, Satisfied, Don’t Know, Somewhat Satisfied, and Not Satisfied. Based on usability engineering evaluations, we will design and prototype BeRo, to create a place for interaction between students, teachers, employees and their environment, literally HCI on environmental scale! Our platforms will be iteratively designed, prototyped and evaluated on real users. In this research, we will present BeRo’s concept, motivations, scenarios of operation, architecture, and the prototype of the selected system. Finally, we will present the heuristic evaluations of BeRo from 4 experts in the field of computation, robotics, and control.