Special Session on
“Artificial Intelligence for Non-Linear Control”

Aim and Scope

Modern engineering systems show increasing complexity due to their high nonlinearity and large disturbances and uncertainties introduced by them. In many cases, conventional mathematical models, such as differential equations that can accurately describe the complex systems and can be exploited in real-life applications, do not exist. However, with the fast development of advanced sensing, measurement, and data collection technologies, a large amount of data that represent input-output relationships of the systems become available. This makes data-driven modelling (DDM) possible and practical. Complex systems such as higher order systems, time-delay systems and large interconnected systems are better represented using artificial intelligent techniques like reinforcement learning, neural network and fuzzy logic. Recently researchers use an initial approximate model with a prior information and use artificial intelligent techniques to update the model using online data. This approach using artificial intelligent techniques has been widely used in numerous industries and fields such as healthcare, transportation, education, electronic trading, finance, gaming, e-commerce, medical diagnosis, cyber defense, remote sensing, robot control and so on. Moreover, many research groups have started applying deep learning to solve problems of interest in the modeling and nonlinear control of dynamical systems. There are many open questions on how to apply AI/ML/DL in control systems in the topics of modeling, adaptive control, robust control etc. This special session will provide a platform for researchers working in this area to present their work and interact with each other.

We are soliciting papers in the topics of:

  • Modelling of Stochastic and intelligent system
  • AI based system identification
  • Big data analytics for modeling
  • Neural networks (NN) and fuzzy logic control
  • NN based direct and indirect adaptive control
  • Intelligent feedback linearization control: continuous and discrete system
  • Backstepping control
  • NN based predictive control
  • Self organizing fuzzy logic control
  • Modeling of Fuzzy PD/PD/PID control
  • Stability analysis of fuzzy control systems
  • Deep learning for modeling and perception
  • Unsupervised learning in adaptive control
  • Intelligent control of time delay systems
  • Reinforcement learning control
  • Intelligent control of power system and power electronics system
  • Intelligent Robotics and autonomous systems
  • Applications to unmanned aerial systems

Paper Submission

Potential authors may submit their manuscripts for presentation consideration through ICETCI 2023 submission system electronically at , following the conference guidelines. All submissions will go through peer review process. To submit your paper to this special session, you have to choose our special session title on the submission page.

Important Dates

Paper submission deadline: Mar 08, 2023
Mar 30, 2023
Apr 15, 2023
Paper acceptance notification date: June 05, 2023
June 08, 2023
Final paper submission and early registration deadline: June 25, 2023


Prof. Jeevamma Jacob, Professor, NIT Calicut

Dr. Shihabudheen KV, Assistant Professor, NIT Calicut
Email: Mob: +91-7895717079

Dr. Arun Neelimegham, Assistant Professor, NIT Calicut
Email: Mob: +91-8436239866