Bogdan M. Wilamowski

About

Bogdan M. Wilamowski is a leading figure in industrial electronics, computational intelligence, and embedded systems, whose work bridges the gap between advanced neural algorithms and practical, low-cost hardware. His most influential contribution is the development of methods to compensate for sensor and device nonlinearities using neural networks implemented on inexpensive 8-bit microcontrollers. This work, detailed in his highly cited 2010 paper (58 citations), enables complex neural architectures to run on minimal hardware, revolutionizing embedded control. He also pioneered a stable training algorithm for computationally intelligent systems by combining gradient descent with variable-structure-systems techniques (44 citations), offering a robust alternative to conventional backpropagation. As the editor of the comprehensive *Industrial Electronics Handbook* (40 citations), he has shaped the field’s reference literature. His research extends into fuzzy inference systems, sliding mode control, and automated web data mining, demonstrating a rare ability to integrate theory with real-world application. With over 100 publications and a career dedicated to making intelligent systems accessible and efficient, Wilamowski’s work remains essential for engineers and researchers working at the intersection of neural networks and embedded control.

Research Focus

Key Achievements

Top Papers

1. 1
   Compensation of Nonlinearities Using Neural Networks Implemented on Inexpensive Microcontrollers

   58 citations · 2010
2. 2
   Stable training of computationally intelligent systems by using variable structure systems technique

   44 citations · 2000
3. 3
   The Industrial Electronics Handbook - Five Volume Set

   40 citations · 2011
4. 4
   Compensation of Sensors Nonlinearity with Neural Networks

   16 citations · 2010
5. 5
   Automated Data Mining from Web Servers Using Perl Script

   10 citations · 2008
6. 6
   Creating a sliding mode in a motion control system by adopting a dynamic defuzzification strategy in an adaptive neuro fuzzy inference system

   7 citations · 2002
7. 7
   Robotics and Vision

   5 citations · 2005
8. 8
   IEEE article data extraction from internet.

   4 citations · 2009
9. 9
   Training of fuzzy inference systems by combining variable structure systems technique and Levenberg-Marquardt algorithm

   3 citations · 2003
10. 10
    Establishment of a sliding mode in a nonlinear system by tuning the parameters of a fuzzy controller

    2 citations · 2002

Key Collaborators

Contact & Links