Open AccessAdaptive Backsteeping SMC with Cuckoo Search Algorithm for Two Wheeled Self Balancing Robot
Author(s) -
Asst. Pro.Dr.Ekhlas H.Karam,
Noor Mjeed
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.13.16318
Subject(s) - control theory (sociology) , cuckoo search , robustness (evolution) , backstepping , computer science , lyapunov function , sliding mode control , mobile robot , controller (irrigation) , lyapunov stability , robot , adaptive control , artificial intelligence , algorithm , nonlinear system , control (management) , particle swarm optimization , biochemistry , chemistry , physics , quantum mechanics , biology , agronomy , gene
In this paper, a robust Radial Basis Function (RBF) Backstepping Sliding Mode controller (BS-SMC) is successfully developed for the attitude stabilization and tracking the trajectory of two wheeled self-balancing mobile robot under the external disturbance and uncertainty. The design of BS control is derived based on Lyapunov function to ensure the stability of the robot system and the SMC is designed with a switching function in order to attenuate the effects of the disturbances, the auto-adjustable RBF inference system is suggested to estimate the equivalent component of the BS-SMC to treat the model dependency problem and robustness improvement. Also a cuckoo search (CS) optimization algorithm is used to determine the optimal values of the backsteeping sliding mode controller. Numerical simulations show the efficiency of the suggested controller in handling the balance and tracking problems of the two wheeled self-balancing mobile robot