Robust control of mobile robot in presence of disturbances using neural network and global fast sliding mode

Stabilization of Robots With a Regulator Containing the Sigmoid Mapping

“…Authors analyze proportional derivative sliding model regulators of overhead cranes and inverted pendulums in [24]- [26], and [27]. In [28]- [30], and [31], authors addressed robust sliding model regulators of parallel manipulators and quadrotors. Authors discussed regulators for stabilization of multiple converters in [32], [33], and [34].…”

“…The aforementioned research is divided in two big groups where [16]- [19], [21], [22], [24]- [26], [29], [32]- [34] are focused on the stabilization of nonlinear models subject to nonlinear uncertainties, and [9]- [15], [20], [23], [27], [28], [30], [31] are focused on the stabilization of nonlinear models subject to external perturbations. It is important to note that in most of the cases the nonlinear uncertainties or external perturbations are unknown.…”

“…There are other two issues in a regulator that could limit its performance: a) when boundedness of the regulator law terms is not ensured, and b) when chattering of the signum mapping is increased. The mentioned issues are solved in our regulator as following: a) taking into account that the sigmoid mapping is used in a neural network to ensure its boundedness [16]- [19], we use the sigmoid mapping to ensure boundedness of the regulator law terms, b) taking into account that the saturation mapping is used to reduce its chattering without ensuring its stabilization [28]- [31], we reduce the chattering by the usage of the saturation mapping while we ensure the stabilization.…”