Abstract
In this work, an optimization technique is adopted to manipulate the input and output scaling factors of a modular fuzzy logic controller (MFC) for lifting and stabilizing the front wheels of a wheelchair in two-wheeled mode. A virtual wheelchair (WC) model is developed within Visual Nastran (VN) software environment where the model is further linked with Matlab/Simulink for control purposes. The lifting of the chair is done by transforming the first link (Link1), attached to the front wheels (casters) to the upright position while maintaining stability of the second link (Link2) where the payload is attached. General rules of thumb allow heuristic tuning (trial and error) of the parameters but such heuristic method does not guarantee that the system tuned with current data set will represent future system states. A global optimization mechanism such as genetic algorithm is necessary to improve the system performance. Due to its significant advantages over other searching methods, a genetic algorithm approach is used to optimize the scaling factors of the MFC and results show that the optimized parameters give better system performance for such a complex, highly nonlinear two-wheeled wheelchair system.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Computational Intelligence and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
