State feedback based on grey wolf optimizer controller for two-wheeled self-balancing robot

Abstract The two-wheeled self-balancing robot (TWSBR) is based on the axletree and inverted pendulum. Its balancing problem requires a control action. To speed up response of minimize steady state error, in this article, grey wolf optimizer (GWO) method proposed for TWSBR space feedback technique. controller stabilizes minimizes overshoot value system. dynamic model system derived Euler formula linearized to representation enhance Then, GWO optimizes parameters. Simulation results show that reaches zero steady-state error with less than 2 ms, which proves effectiveness over classical terms fast response, very small overall minimum overshoot.