Research
Introduction:-
My research has been in the field of control and power system engineering Cite. Broadly speaking, my main research interests include control theory and applications of systems in the presence of input nonlinearities, anti-windup compensator techniques, synchronization of chaotic systems, nonlinear systems, cascade systems, time-delay systems, distributed control systems, and robust control systems.
RESEARCH AREAS
— Control of Systems with Constraints.
— Synchronization of Chaotic System.
— Consensus Control for Multi-agent Systems.
— Networked Control System (NCS).
— Power System Control and Stability.
Control of Systems with Constraints
Determination of controllers for dynamical systems becomes a more and more arduous task as specifications and requirements become more and more stringent. With respect to the system's required performances, controllers built by using standard tools of linear analysis and synthesis result in high control efforts. However, any physical system is submitted to operation limitations induced by physical, technological, or even security considerations. These limitations are mainly associated with the amplitude constraints of actuators and sensors. Hence, controllers formed without taking into account these limitations a priori may lead to undesirable or even disastrous process behavior, such as loss of stability.
In the better case, the pre-specified performances required to derive the controller will no longer be satisfied if some actuators saturate, because of, for example, perturbations or a setpoint change.
The closed-loop system may also evolve towards some other operation state with the risk that when the saturation ends, it cannot come back to the expected operating state. Motivations and interests in the analysis and synthesis of controllers for systems submitted to nonlinearities (saturations) on both actuators and sensors originate from those practical problems. Actuator saturation is one of the common nonlinearities present in various control systems. Which can limit the performance of a closed-loop system with undesirable results like large overshoots, large settling time, lag and instability, etc. It has caused accidents of power plants and many air-crafts.
Synchronization of Chaotic System (Robust and Adaptive Control)
Synchronization of two or more systems in the form of drive and response architecture is an important subject in science and engineering. This synchronization phenomenon plays a vital role in a variety of real-world situations and has wide applications associated with these situations. Some of these applications are high power lasers applications, secure information transmission, multiple power generators synchronization, synchronization of two gyros, synchronization of electro-mechanical systems, synchronization of robots, ships, submarines, and aircraft, and synchronization of biological oscillations.
Robust-adaptive synchronization of drive and response systems using coupled chaotic adaptive synchronous observers is studied in []. The authenticity of the proposed amendments is validated by the simulation of synchronization of the FitzHugh-Nagumo neural drive and response system under the effect of disturbances and noise. The adaptive synchronization technique for chaotic systems with nonlinear coupling and unknown parameters is proposed in []. The proposed adaptive synchronization technique is successfully applied to synchronize two common chaotic systems, the Röseller system, and the modified Chua’s circuit. Robust synchronization of chaotic nonlinear systems with modeling uncertainties, unmeasured states, input constrained, and external disturbances by employing nonlinear observers-based chaos synchronization methodology have been proposed in the article [].
Consensus Control of Multi-agent Systems
Consensus means the interaction between groups of agents in a team, via sensors or a communication network, to reach an agreement on a common value or state. A consensus is a special case of multi-agent coordination, that is, the agreement of agents on some quantity of interest or, more generally, the full or partial synchronization of their state trajectories. Consensus dynamics or agreement dynamics is an area of research lying at the intersection of systems theory and graph theory. A major topic of investigation is the agreement or consensus problem in multi-agent systems that concerns processes by which a collection of interacting agents achieves a common goal.
We have investigated a local observer-based leader-following consensus control of one-sided Lipschitz (OSL) multi-agent systems (MASs) under input saturation. The proposed consensus control scheme has been formulated by using the OSL property, input saturation, directed graphs, estimated states, and quadratic inner-boundedness condition by attaining the regional stability. It is assumed that the graph always includes a (directed) spanning tree with respect to the leader root to develop matrix inequalities for investigating parameters of the proposed observer and consensus protocols. Further, a new observer-based consensus tracking method for MASs with saturation, concerning independent topologies for communicating outputs and estimates over the network, is explored to deal with a more perplexing and realistic situation. In contrast to the traditional methods, the proposed consensus approach considers output feedback and deals with the input saturation for a generalized class of nonlinear systems.
MS Students:
1.— Jawad Bahadur Khan, 2021-2023, “Consensus Control of Multi-agent System”, Department of Electrical & Computer Engineering, Air University, Islamabad.
2.— Khushal Khan, 2021-2023, “Event Trigger Based Model Predictive Control Design for Dynamical Systems. ”, Department of Electrical & Computer Engineering, Air University, Islamabad.
3.— Qundeel Baber, 2021-2023, “Intelligent Control System Design. ”, Department of Electrical & Computer Engineering, Air University, Islamabad.
4.— Iraj Rashid, 2021-2023, “Robust Distributed Control of Discrete-time Nonlinear Systems with Time Delay. ”, Department of Electrical & Computer Engineering, Air University, Islamabad.
We are currently working on a traffic signs detection-recognition-tracking system.
This work is done in collaboration with LE2I (France - Le Creusot) under supervision of Yohan Fougerolle.
Our contribution is threefold:
Proposition of a new naive detection based on color and shape retrieval.
Using the information of the detection, we propose to recognize traffic sign using machine learning methods.
In order to perform to accelerate the process of detection-recognition, we propose to introduce a tracking module information already extracted in the two previous stages.
The source code of this implementation is available in GitHub.
We develop a method allowing to track any kind of object inside a video.
Our method belongs to the group of features-based tracking method. In fact, features are detected in two consecutive images and correspondences are found.
Geometric transformation is estimated using the previous matching by the aid of a robust estimator.
The method proposes the following advantages:
Real-time computation.
Scale invariant.
Rotation invariant.
Partially robust to illumination changes.
Partially robust to occlusions.
More details can be found in the above publication:
G. Lemaitre, E. Vargiu, J.A. Lorenzo Fernández and F. Miralles,
"Real-Time 2D Face Detection and Features-based Tracking in Video",
IADIS Multi Conference in Computer Science in Computer Graphics, Visualization, Computer Vision and Image Processing 2012. Lisbon: Portugal (July 2012)
Pruning AdaBoost for Continuous Sensors Mining Applications
In this paper, pruning techniques for the AdaBoost classifier are evaluated specially aimed for continuous learning in sensor mining applications. To assess the methods, three pruning schemes are evaluated using standard machine-learning benchmark datasets, simulated drifting datasets and real world cases.
Early results obtained show that the pruning methodologies approach and sometimes out-perform the no-pruned version of the classifier, being at the same time more easily adaptable to the drift in the training distribution.
Future works are planned in order to evaluate the approach in terms of time efficiency and big-data extensions.
More details can be found in the above publication:
M. Rastgoo, G. Lemaitre, X. Rafael, F. Miralles and P. Casale,
"Pruning AdaBoost for Continuous Sensors Mining Applications",
Ubiquitous Data Mining Workshop, 20th European Conference in Artificial Intelligence 2012. Montpellier: France (August 2012)