This paper describes the modeling of a wheeled inverted pendulum type mobile robot driven by two different wheels for the posture and velocity control. In order to control its posture and velocity, the optimal linearized modeling is quite crucial.
Meta-heuristics is a term used to characterize a number of methods which have been proven to be practical and effective algorithms for solving nonlinear problems.
This paper adapted the wheeled inverted pendulum type mobile robot which is typically nonlinear systems identification and linearization techniques, using a real-coded genetic algorithm. The algorithm is finely tuned by simulated annealing, which yields a faster convergence and a more accurate search.
By applying this method, the nonlinear model is transformed into a completely linearized system.