Backstepping Control of Nonlinear Dynamical Systems addresses both the fundamentals of backstepping control and advances in the field. The latest techniques explored include 'active backstepping control', 'adaptive backstepping control', 'fuzzy backstepping control' and 'adaptive fuzzy backstepping control'. The reference book provides numerous simulations using MATLAB and circuit design. These illustrate the main results of theory and applications of backstepping control of nonlinear control systems. Backstepping control encompasses varied aspects of mechanical engineering and has many different applications within the field. For example, the book covers aspects related to robot manipulators, aircraft flight control systems, power systems, mechanical systems, biological systems and chaotic systems.
This multifaceted view of subject areas means that this useful reference resource will be ideal for a large cross section of the mechanical engineering community.
0
Prof. Ahmad Azar is a full Professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is the leader of Automated Systems and Computing Lab (ASCL), Prince Sultan University, Saudi Arabia.
Prof. Azar is the Editor in Chief of the International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. He is also the Editor in Chief of International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) and International Journal of Sociotechnology and Knowledge Development (IJSKD) published by IGI Global, USA. From 2013 to 2017, Prof. Azar was an associate editor of ISA Transactions, Elsevier.
He is currently an editor for IEEE Transactions on Fuzzy Systems, IEEE Systems Journal, IEEE Transactions on Neural Networks and Learning Systems, Springer's Human-centric Computing and Information Sciences.
Prof. Azar specializes in artificial intelligence (AI), robotics, machine learning, control theory and applications, computational intelligence, reinforcement learning, and dynamic system modeling. He has published or co-published over 550 research papers, book chapters, and conference proceedings in prestigious peer-reviewed journals.
Dr. Ahmad Azar has received several awards, including the Benha University Prize for Scientific Excellence (2015, 2016, 2017, and 2018) and the Benha University Highest Citation Award (2015, 2016, 2017, and 2018).
In June 2018, he was awarded the Egyptian State Encouragement Award in Engineering Sciences by the Ministry of Higher Education and Scientific Research. In August 2018, he was elected as a senior member of the International Rough Set Society (IRSS).
Prof. Azar was named one of the top computer scientists in Saudi Arabia by Research.com since December 2019.
He was awarded the Egyptian President's Distinguished Egyptian Order of the First Class in February 2020.
In October 2020, Prof. Azar received Abdul Hameed Shoman Arab Researchers Award in Machine Learning and Big Data Analytics.
From October 2020 to September 2023, Prof. Azar was recognized as a Distinguished researcher at Prince Sultan University, Riyadh, Saudi Arabia.
In November 2020, October 2021, October 2022, October 2023, September 2024, and September 2025 Prof. Azar was named one of the top 2% of scientists in the world in Artificial Intelligence by Stanford University, based on single-year impact and career-long impact. These rankings were published by Stanford University in the PLOS journal and were based on the SCOPUS database.
Prof. Ahmad Azar has been recognized as one of the top ten researchers at Prince Sultan University, based on his Scopus H-index. He has also received a university award for being among his top publication of research.
Prof. Azar has received Prince Sultan University’s Research Excellence Award. He is also the recipient of the university’s Highest Impact Researcher Award, based on his H-index. Additionally, he has earned a PSU research award for having publications ranked among the top five by impact factor.
Prof. Ahmad Azar is the Vice Chair of the International Federation of Automatic Control (IFAC) Technical Committee of Control Design, Vice chair of IFAC Technical committee 4.3 Robotics, Vice chair of IFAC Technical committee 9.3 “Control for Smart Cities”. He is a technical Committee Member of Data Mining and Big Data Analytics of IEEE Computational Intelligence Society (CIS), IFAC Technical committee Member TC 2.2. Linear Control Systems, IFAC Technical committee Member TC 1.2. Adaptive and Learning Systems.
