Researcher | University of Tunis El Manar | Tunisia
Dr. Farouk Zouari is a distinguished researcher specializing in Electrical Engineering, Artificial Intelligence, Adaptive Control, and Computer Engineering, recognized for his pioneering contributions to intelligent control of nonlinear, fractional-order, and chaotic systems. His research primarily focuses on advanced neural and fuzzy control, time-delay system modeling, nonlinear system stabilization, and innovative output-feedback strategies, while his emerging interests explore AI-driven decision algorithms, intelligent medical control systems, and adaptive synchronization of complex dynamic systems. Dr. Zouari has served in key academic and research roles, collaborating extensively with multidisciplinary teams to develop next-generation control architectures, neural approximators, observer-based feedback systems, and high-precision adaptive controllers that strengthen both theoretical frameworks and real-world engineering applications. His contributions include novel designs for neural network controllers, intelligent fuzzy synchronization mechanisms, adaptive quantized control schemes, and robust backstepping approaches that address actuator nonlinearities, pseudo-state constraints, and fractional-order uncertainties. He has also advanced event-triggered control, intelligent drug-dosage dynamic modeling, and optimal control of electromechanical systems, providing impactful innovations with industrial, biomedical, and automation-related applications. Dr. Zouari’s growing body of research has resulted in high-impact publications that are widely cited for their methodological rigor and technical depth, contributing significantly to advancing nonlinear system control, computational intelligence, and real-time dynamic system optimization. His work has supported new engineering solutions, informed emerging policies on intelligent automation, and inspired further exploration into hybrid AI-control paradigms for next-generation autonomous systems. Driven by a deep commitment to scientific progress, his vision centers on integrating adaptive intelligence into complex engineering infrastructures to enhance efficiency, safety, and resilience across industries. He aims to bridge theoretical advancements with scalable real-world innovations, strengthening global research in intelligent control and enabling transformative technologies that benefit society through smarter automation, precision medical systems, and sustainable intelligent engineering solutions.
Featured Publications
1. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2018). Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities. Neural Networks, 105, 256–276.
2. Boubellouta, A., Zouari, F., & Boulkroune, A. (2019). Intelligent fuzzy controller for chaos synchronization of uncertain fractional-order chaotic systems with input nonlinearities. International Journal of General Systems, 48(3), 211–234.
3. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2021). Neural network controller design for fractional-order systems with input nonlinearities and asymmetric time-varying pseudo-state constraints. Chaos, Solitons & Fractals, 144, 110742.
4. Zouari, F., Boulkroune, A., & Ibeas, A. (2017). Neural adaptive quantized output-feedback control-based synchronization of uncertain time-delay incommensurate fractional-order chaotic systems with input nonlinearities. Neurocomputing, 237, 200–225.
5. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2019). Neuro-adaptive tracking control of non-integer order systems with input nonlinearities and time-varying output constraints. Information Sciences, 485, 170–199.
