Speaker: Prof. Enrique V. Carrera, Armed Forces University, Ecuador
Date: February 15, 2022, 6:00 PM (PST)
Presentation Slides: (50:04 + Q&A)
Summary: During the design of control systems, the adjustment of the controller parameters plays a fundamental role in the performance of the transient and steady-state regimes. From this perspective, the tuning of controller parameters has been performed using various methods and tools, but recently, meta-heuristic algorithms have improved tuning procedures to ensure the operation and stability of those systems. Thus, optimization algorithms that mimic the evolution of self-organizing biological systems, also called nature-inspired algorithms, have gained great relevance due to their significant potential for solving optimization problems. In particular, this talk presents the basics of several nature-inspired optimization algorithms and their application to tune the parameters of the fuzzy logic controller of a nonlinear magnetic levitation system, and an energy management system for a residential microgrid. Various results are provided to highlight and compare the features of the optimized controllers.
Enrique V. Carrera received his bachelor’s degree in electronic engineering from the Armed Forces University, Ecuador, in 1992, and his master’s degree in electrical engineering from the Pontifical Catholic University of Rio de Janeiro, Brazil, in 1996. In 1999, he received his doctorate in computer engineering from the Federal University of Rio de Janeiro, Brazil. He was a visiting scholar at the University of Rochester, USA, in 1999. From 2000 to 2004, he was a postdoctoral associate in the Department of Computer Science at Rutgers University, USA. Since 2011, he has been a professor at the Armed Forces University, Ecuador. He has also collaborated as an external professor at King Juan Carlos University, Spain, since 2014. Currently, he is an IEEE Senior Member and has an appointment as a Distinguished Visitor at the IEEE Computer Society. His main research areas include signal processing and computational intelligence.