Sliding Mode Control of Nonlinear Systems With Input Distribution Uncertainties

Abstract

In this paper, a sliding mode control design method is developed for a class of fully nonlinear systems in generalized regular form, where both input distribution uncertainty and system uncertainties are considered. Based on the generalized regular form, a novel nonlinear sliding surface is designed and uniform ultimate stability of the corresponding sliding mode dynamics is analyzed. Then, under the assumption that the uncertainties are bounded by known nonlinear functions of the system states, a sliding mode controller is formulated to ensure that the dynamical system reaches the sliding surface in finite time even in the presence of the system uncertainties and input distribution uncertainties. Further, for the case of system uncertainty with unknown bound in parameterized form, an adaptive sliding mode controller is developed to drive the dynamical system to the sliding surface and maintain a sliding motion thereafter. The developed sliding mode controller is applied to a High Incidence Research Model (HIRM) aircraft model. Simulation results demonstrate that the developed methods are effective.

Distributed adaptive control for multiple unmanned aerial vehicles with state constraints and input quantization

“…Previously, many approaches to solve the adverse effect of unknown failures have been proposed. In Reference 13, the finite time control problem of a class of fully nonlinear aircraft systems with both system uncertainties and input distribution uncertainties is studied, a novel nonlinear sliding manifold is constructed to compensate the multiple sources of uncertainties in aircraft dynamics. In Reference 14, an event‐triggered reinforcement learning (RL) control strategy is presented to stabilize the quadrotor UAV with actuator saturation.…”